Application Development Lead Analyst Position Overview:This position’s primary responsibility will be to translate software requirements into functions using Mainframe, ETL frameworks, Database technologies. The chosen candidate will apply technical proficiency across different stages of the Software Development Life Cycle, gather accurate requirements and work closely with stakeholders to prioritize his tasks. The role will require strong attention to detail with the ability to identify errors and make adjustments in a testing environment while contributing towards developing and adhering to best practices for developing applications that are scalable, relevant, and critical to the project. Responsibilities:<ul><li>Support, maintain and participate in the development of software utilizing technologies such as COBOL, DB2, CICS and JCL. </li><li>Support, maintain and participate in the ETL development of software utilizing technologies such as Talend, Abinitio, AWS Glue, PySpark, Python</li><li>Provide expertise, tools, and assistance to operations, development, and support teams for critical production issues and maintenance </li><li>Troubleshoot production issues, diagnose the problem, and implement a solution - First line of defense in finding the root cause </li><li>Work cross-functionally with the support team, development team and business team to efficiently address customer issues. </li><li>Active member of high-performance software development and support team in an agile environment. </li></ul> QualificationsRequired Skills:<ul><li>Strong Mainframe experience, using Cobol, JCL, DB2 and VSAM</li><li>Strong SQL knowledge on OLAP DB platforms (Teradata, Snowflake) and OLTP DB platforms (Oracle, DB2, Postgres, SingleStore)</li><li>Strong experience with Teradata SQL and Utilities</li><li>Strong experienced with Oracle, Postgres and DB2 SQL and Utilities</li><li>Develop high quality database solutions</li><li>Ability to do extensive analysis on complex SQL processes and design skills</li><li>Ability to analyze existing SQL queries for performance improvements</li><li>Experience in ETL frameworks like Talend or Abinitio or AWS Glue.</li><li>Experience in software development phases including design, configuration, testing, debugging, implementation, and support of large-scale, business centric and process-based applications </li><li>Proven experience working with diverse teams of technical architects, business users and IT areas on all phases of the software development life cycle. </li><li>Exceptional analytical and problem-solving skills </li><li>Structured, methodical approach to systems development and troubleshooting </li><li>Ability to ramp up fast on a system architecture </li><li>Experience designing and developing process-based solutions or BPM (business process management) </li><li>Strong written and verbal communication skills with the ability to interact with all levels of the organization. </li><li>Strong interpersonal / relationship management skills. </li><li>Strong time and project management skills. </li><li>Familiarity with agile methodology including SCRUM team leadership. </li><li>Familiarity with modern delivery practices such as continuous integration, behavior/test driven development, and specification by example. </li><li>Desire to work in application support space </li><li>Passion for learning and desire to explore all areas of IT</li></ul> Required Experience & Education: <ul><li>6+ years in an application development role </li><li>Bachelor's Degree or higher from an accredited university or a minimum of three (3) years of experience in software development in lieu of the bachelor’s degree education requirement </li></ul> Desired Experience:<ul><li>Exposure to AWS </li><li>Healthcare experience </li></ul> Location & Hours of Work:<ul><li>Full-time position, working 40 hours per week. Expected overlap with US hours as appropriate. </li><li>Primarily based in the Innovation Hub in Hyderabad, India, with flexibility to work remotely as required.</li></ul>

Required Education and Experience:<ul><li>Bachelor's degree in Computer Science, MIS, or related field</li><li>7+ years of experience with SQL & data engineering techniques.</li><li>7+ years of experience building data integration solutions using tools like Informatica, Talend, Mulesoft, Qlik, etc.</li><li>3+ years of experience leading engineering resources</li><li>Strong experience in working with heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using various data integration technologies (ETL/ELT, data replication/CDC, message-oriented data movement, API design, etc.)</li><li>Experience with DevOps, CI/CD pipelines and Databricks</li><li>Hands on experience with programming languages such as Python, SQL to create automated processes for data gathering, cleansing, reporting, and visualization</li><li>Experience in working with Cloud data warehouse like Snowflake, AWS Redshift, Azure Synapse or Google BigQuery.</li><li>Collaborate with cross functional team to resolve data quality and operational issues.</li><li>Demonstrating best practices for code development and optimization, unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response in order to ensure data availability, data quality, usability and required performance.</li></ul> Required Competencies / skills:<ul><li>Ability to obtain a clear understanding of business needs and value, mapping out the solution, and working on its implementation.</li><li>Ability to collaborate across all levels and areas of the product & business team as well as perform hands-on implementation.</li><li>Excellent communication, presentation, and documentation skills, including the ability to distill highly technical concepts and communicate them effectively to non-technical stakeholders</li><li>Capable of using agile methodology and implementing Continuous Integration/Continuous Delivery (CI/CD) pipelines</li><li>Exposure to data vault method, model, and architecture</li><li>Ability to monitor the overall data landscape: meta data, processing patterns, and data quality</li><li>Ability to work closely with developers and data analysts to design and optimize data access, query, reporting and analysis strategies to solve complex business problems</li><li>Ability to proactively communicate and manage technology and projects risks</li><li>Troubleshooting skills, ability to determine impacts, ability to resolve complex issues, and ability to exercise sound judgment and initiative in challenging situations</li><li>Perform root cause analysis when there are issues</li><li>Ability to proactively communicate and manage technology and projects risks</li><li>Troubleshooting skills, ability to determine impacts, ability to resolve complex issues, and ability to exercise sound judgment and initiative in challenging situations.</li></ul> Preferred Education and Experience:<ul><li>Bachelor’s or Master’s degree in Business Analytics, Computer Science, Mathematics, Statistics, or a related discipline; or an equivalent combination of demonstrated skills and experience</li><li>Experience working with Qlik technologies (Replicate and Compose)</li><li>Experience with any scripting languages, preferably Python</li><li>Experience working using agile methodologies</li><li>Experience in Manufacturing, Retail or Agriculture industry</li></ul> Preferred Competencies / Skills:<ul><li>Ability to work closely with business partners to influence decisions on technology investments</li><li>Ability to provide technical leadership to evangelize best practices/proven patterns and promote the use of Corporate IT standards</li><li>Working knowledge of data privacy regulations including GDPR and CCPA as well as how to design solutions to drive compliance</li></ul>

Role: Data EngineerThe data engineer will design solutions and work with a team of engineers to ensure accurate, consistent, reliable, and sustainable solutions are delivered. The data engineer will also influence data engineering processes that result in highly accurate and trusted data assets for use in Truterra and across the organization. Required Education and Experience:<ul><li>Bachelor's degree in Computer Science, MIS, or related field with 4+ years of experience.</li><li>Applicable experience is characterized as advanced SQL, data engineering & data modeling techniques</li><li>3+ years of experience building data integration solutions using tools like Informatica, Talend, Mulesoft, Qlik, etc.</li><li>Strong experience building out data warehouse and/or data lake</li><li>1+ years of experience working with cloud-native data solutions on Microsoft Azure, AWS, or Google Cloud platform</li><li>Strong experience leading full lifecycle, large, complex reporting or data engineering efforts</li><li>Strong experience in working with heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using various data integration technologies (ETL/ELT, data replication/CDC, message-oriented data movement, API design, etc.)</li><li>Experience with DevOps, CI/CD pipelines and automated testing</li></ul> Required Competencies / skills: <ul><li>Implement data structures using standards and best practices in data modeling, ETL/ELT processes, SQL, database, and other technologies</li><li>Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.</li><li>Thorough experience building and optimizing data pipelines and data sets.</li><li>Deep knowledge of the data vault method, model, and architecture</li><li>Ability to manage the overall data landscape: meta data, processing patterns, and data quality</li><li>A successful history of manipulating, processing and extracting value from large datasets.</li><li>Strong working knowledge of message queuing, stream processing, and highly scalable data stores</li><li>Ability to obtain a clear understanding of business needs and value, developing a detailed vision for the initiative, mapping out the solution, and guiding its implementation</li><li>Develop test-driven solutions that can be deployed quickly and in an automated fashion</li><li>Ability to obtain a clear understanding of business needs and value, developing a detailed vision for the initiative, mapping out the solution, and guiding its implementation</li><li>Demonstrated ability to collaborate across all levels (Engineers, Management, Architects, etc.) & across all skill sets (Data scientists, Data visualization developers, Salesforce developers etc.) particularly in a Product-oriented culture</li><li>Excellent communication, presentation, and documentation skills, including the ability to distill highly technical concepts and communicate them effectively to non-technical stakeholders</li><li>Demonstrated ability to develop and maintain trusted-advisor status to technology and business stakeholders at various levels</li><li>Capable of using agile methodology and implementing Continuous Integration/Continuous Delivery (CI/CD) pipelines</li><li>Ability to proactively communicate and manage technology and projects risks</li><li>Troubleshooting skills, ability to determine impacts, ability to resolve complex issues, and ability to exercise sound judgment and initiative in challenging situations.</li></ul> Preferred Education and Experience:<ul><li>Bachelor’s or Master’s degree in Business Analytics, Computer Science, Mathematics, Statistics, or a related discipline; or an equivalent combination of demonstrated skills and experience</li><li>Experience working with Databricks (or Spark) & Qlik technologies (Replicate and Compose)</li><li>Experience with any scripting languages, preferably Python</li><li>Experience working with BI Tools (Power BI, Tableau etc.) to create dashboards and reports</li><li>Experience with Snowflake</li><li>Experience working using agile methodologies</li><li>Experience in Manufacturing or Agriculture industry</li></ul> Preferred Competencies / Skills:<ul><li>Ability to work closely with business partners to influence decisions on technology investments</li><li>Engage and evangelize best practices/proven patterns and promote the use of Corporate IT standards</li><li>Working knowledge of data privacy regulations including GDPR and CCPA as well as how to design solutions to drive complia</li></ul>

Technology at Brit:Brit has a leadership position at Lloyd’s, the most well-known insurance market in the world. At Brit, we believe that the uncertainty of the future should never stand in the way of progress. That’s why we exist. To help people and businesses face the future and thrive.We are change-makers enabled by a global workforce who collaborate to deliver a risk service. Our goal is to attract and retain the best talent in the market and empower those individuals to innovate, and champion the strategic objectives within the business. Our technology and data teams have led some of the most noteworthy developments in the London market, by delivering digital, data and AI driven capabilities: Data is a key capability to drive Brit’s ambition for digital, innovation, growth and efficiencies. Brit leads the market with respect to our data modernisation journey, delivering on our vision to build a central, trusted, cost efficient, flexible, and scalable cloud native data platform that enables us to harness maximum value from internal and external data for Brit. Brit is active in advancing digital trading approaches, most notably with respect to Broker APIs. At Brit, we are designing a multi class of business headless API which connects Brits pricing and document generation to multiple global Broker platforms, Market Hubs, and enables bulk submission ingestion. Brit has launched its Underwriting Transformation journey advancing our capabilities deploying digital foundations for pricing and underwriter workbench. Brit’s new modern Underwriting Platform is at the heart of this transformation agenda, with a focus on engineering, upskilling in python, exploring ingestion and analytics, we are actively delivering our digital future.Our market leading proprietary machine learning algorithm designed to accelerate the identification of post catastrophe property damage, based on the use of ultra-high-resolution imagery, allows Brit to accelerate service to its customers when they need it most, noted as the first enabler for virtual claims adjusting in the London market. We value continuous learning & exploration, encouraging our people to constantly evolve and take advantage of the best-in-class technology & tooling.If you have the drive to work in a flexible, fun, passionate Technology and Data team we would love to hear from you! Purpose of the Job:As a Data Engineer, the role holder will be responsible for operating within a team of data engineers that build and run the core components of an effective Azure Data Lake platform; encompassing key services such as Azure Blob Storage, Azure Data Factory, Synapse, Databricks, SQL Data Warehousing and PowerBI for end-user data analytics and reporting. This role will play an engineer role in the continuous utilisation, expansion, and refinement of these services, as well as the development of critical data models - capable of meeting a wide range of financial and underwriting reporting/analytics needs. This role will encompass a mix of data engineering and BI development skills. As a Data Engineer, the role holder will:<ul><li>Design, develop, and hold accountability for core data engineering services, such as data orchestration and CICD pipelines </li><li>Design and develop ETL/ELT processes, data lake architecture, data warehouse databases, data marts, cubes, reports and dashboards; in-line with company reporting strategy and best practise</li><li>Design and develop models and databases both relational and dimensional to support reporting requirements.</li><li>Create reporting solutions in line with standards, architectural principles and practices</li><li>Assess change impact assessment on live systems and processes</li><li>Work in an agile, proactive manner; delivering high quality solutions in agreed timescales</li><li>Mentor and support junior data engineers/developers in the team</li></ul> Principal Accountabilities:<ul><li>Contributor on the design and build of Brit’s enterprise strategic reporting solutions covering all components of Brit’s data lake/MI/BI platform architecture and adhere to coding practices/standards</li><li>Document technical design and analysis work.</li><li>Develop and Support applications in Azure </li><li>Assess business requirements and build reporting solutions to meet business needs</li><li>Follow and enforce SDLC best practices, standards and design principles covering all aspects of data lifecycle management and BI/MI solutions</li><li>Assist in developing standards for data lakes, data ingestion, data access layers and BI solutions</li><li>Ensure that adequate steps are taken to protect data and the Brit data platform</li><li>Ensure that all new BI/MI requirements are met using the most appropriate architecture components</li><li>Design appropriate BI/MI solutions to meet business needs</li><li>Ensure Brit maintains a low technical debt & identify area(s) for automation and continuous improvement</li><li>Work in a DevOps team - will involve being available on call and supporting out of office hours</li><li>Develop working software to a good standard using recognized software engineering principals whilst adhering to Brit development standards.</li><li>Deliver features in a timely fashion within approved deadlines during IT projects.</li></ul> Regulatory Conduct Rules:<ul><li>Act with integrity.</li><li>Act with due skill, care and diligence.</li><li>Be open and co-operative with Lloyd’s, the FCA, the PRA, and other regulators.</li><li>Pay due regard to the interests of customers and treat them fairly. </li><li>Observe proper standards of market conduct. </li></ul> Education, Qualifications, Knowledge, Skills and Experience:Required Skills & Knowledge<ul><li>Solid hands-on experience with Azure Data Lake (incl. Blob Storage, Delta) Azure Data Factory, Synapse and Databricks</li><li>Proven experience of SQL/Azure SQL data warehousing</li><li>Proven experience of data engineering activities such as release management, environment controls, CICD pipeline orchestration</li><li>Experience working with Python and Spark</li><li>Proven ability of Microsoft BI software development including database / reporting development, full development cycle</li><li>Strong data modelling, problem solving, information analysis, attention to detail, flexibility of approach</li><li>The ability to deal directly with business functions and interpret their thoughts into successful data & analytics solutions</li><li>The ability to design and develop complex BI/MI solutions in line with agreed architectural principles and toolsets.</li><li>Capable of working closely with the business and delivering complex requirements to tight timescales.</li><li>Strong interest in latest data engineering technologies, best practices, techniques and trends in the data industry</li></ul> Required Toolsets:<ul><li>Azure Data Lake Storage, Analysis Services (Multidimensional/Tabular), Power BI, Azure Data Factory, Synapse, Azure Databricks/Spark</li><li>Microsoft SQL Server or Azure SQL DB</li><li>Kimball data modelling</li></ul> Desirable Skills and Knowledge:<ul><li>Knowledge of London market insurance</li><li>Extensive experience in the design and build of data warehouse/data lake</li><li>Experience working with financial systems and business processes</li><li>Experience of cloud architectures and solutions, especially Azure</li><li>Experience of Infrastructure-as-Code e.g. Terraforms</li><li>Agile development techniques (SCRUM, Kanban etc)</li></ul> Desirable Toolsets:<ul><li>Python, MDX, DAX</li><li>Azure DevOps</li></ul> Required Qualifications:<ul><li>Degree Level or above (Science, Maths, Computing, Engineering or related subject preferred)</li></ul>

Senior Data Engineer JOB DUTIES:<ul><li>Design and architect data lake solutions on AWS S3 and Snowflake, considering scalability, automation, security, and performance requirements.</li><li>Responsible for architecting, building, and optimizing data lake to store, process and analyze large volumes of structure and unstructured data.</li><li>Requirements gathering and analysis, development planning and co-ordination, data testing, documentation and ensuring high levels of data quality is maintained.</li><li>documentation.</li><li>Work with project leads, stakeholders, and business SMEs to define technical specifications to develop data integration requirements, code design and functional and technical documentation.</li><li>Work with specifications to design, develop, and maintain data infrastructure.</li><li>Work with cross functional teams and process owners on the development of test cases and scripts, test models and solutions to verify that requirements are met and ensuring high levels of data quality.</li><li>Promote and apply quality assurance best practices.</li><li>Understand and comply with data governance and compliance practices as defined for risk management. This includes data encryption practices, RBAC and security policies.</li><li>Promote and apply metadata management best practices supporting enterprise data catalogs.</li><li>Excellent problem-solving skills and ability to troubleshoot complex data engineering issues.</li><li>Benchmark application operational performance periodically, track (metrics) and fix issues.</li><li>Support change and release management processes.</li><li>Support incident and response management including problem solving and root cause analysis, documentation.</li><li>Support automation and on-call processes (Tier 1 / Tier 2).</li></ul> SPECIFIC SKILLS OR OTHER REQUIREMENTS: <ul><li>Requires 5 + years of experience with-</li><li>Primary Experience: Data Lakes and Data Integrations</li></ul> Data Engineering:<ul><li>AWS: 4+ years of required expertise with AWS services like S3, Glue, Lambda, EMR, Athena and proficiency in programming languages/ tools like Python, Scala, SQL.</li><li>Apache Software: 2+ years of required expertise in data processing with Spark & Flink, message broking using Kafka, orchestration using Airflow, processing high data volumes in open table formats like Iceberg.</li><li>Snowflake: 3+ years of required expertise with Snowflake SnowSQL, Snowpipe, (integrated with AWS S3), Streams and Tasks, Stored Procedures (expertise working with merge statements), Compute and Storage usage optimizations, Performance optimizations.</li><li>HVR (Fivetran): Near Real-time Data Replications with HVR is a plus.</li><li>SnapLogic: Data integrations with SnapLogic integration platform is a plus.</li><li>Certifications: AWS and Snowflake data engineering certifications is a plus.</li></ul> Data Platforms:<ul><li>Required: AWS S3 data lake store platform, Snowflake cloud data platform</li><li>Preferred: Denodo, SAP HANA</li></ul> Programming/ Scripting:<ul><li>Snowflake: SQL Scripting (Snowpipes, Tasks, Streams, Merge Statements, Stored Procedures, Functions, Security Policies – DDM, Row-Access), SQL Scripting, Python</li><li>AWS: Apache spark, Python</li></ul> Data Orchestration:<ul><li>Preferred: Control-M, Apache Airflow</li></ul> Cloud Storage Platforms:<ul><li>Required: Amazon Web Services</li><li>Preferred: Microsoft Azure</li></ul> Sr Data Engineer <ul><li>Required: Knowledge and experience integrating data from SAP ERP (On premises, Cloud), Salesforce CRM, Workday, Planisware, Team Center PLM, Relational databases, REST APIs</li><li>Preferred: ServiceNow, MFG MES, IOT/ Sensor data platforms, Unstructured data, Other SaaS Applications</li></ul> Data Operations: Excellent understanding of Data Ops practices for data management. Stakeholder Engagement: Ability to take the lead and drive project activities collaborating with Analytics stakeholders and ensure the requirement is completed.Solution Design: Good understanding of end-to-end solution architecture and design practices, ability to document solutions (maintain diagrams) Governance: Good understanding of working with companies having regulated systems and processes for data. Adherence to data protection practices using tagging, security policies and data security (object-level, column-level, row-level). Data Warehousing: Good understand on how data onboarded in the data lakes is used to support data warehouses. Impact of risks and change to a data warehouse. Fundamental concepts of dimensional modeling, experience working on data warehouse solutions, requirement gathering, design & build. Data As-A-Product: Preferred knowledge and experience working with data treated as data products. is following a hybrid data mesh architecture which promotes data as a product for data lifecycle management. Operating Systems: Windows, Linux EDUCATION & EXPERIENCE:Bachelor’s degree equivalent in Computer Science/Engineering or equivalent degree.

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