Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Apache Airflow. Key Responsibilities: <ul> <li>Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.</li> <li>Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements.</li> <li>Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring.</li> <li>Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable data solutions.</li> <li>Optimize data pipelines for performance, reliability, and cost-effectiveness, leveraging AWS best practices and cloud-native technologies.</li> </ul>Requirements <ul> <li>8+ years of experience building and deploying large-scale data processing pipelines in a production environment.</li> <li>Hands-on experience in designing and building data pipelines on AWS cloud infrastructure.</li> <li>Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.</li> <li>Strong experience with Databricks and Apache Spark for data processing and analytics.</li> <li>Hands-on experience with Apache Airflow for orchestrating and scheduling data pipelines.</li> <li>Solid understanding of data modeling, database design principles, and SQL and Spark SQL.</li> <li>Experience with version control systems (e.g., Git) and CI/CD pipelines.</li> <li>Excellent communication skills and the ability to collaborate effectively with cross-functional teams.</li> <li>Strong problem-solving skills and attention to detail.</li> </ul> Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world. We are seeking an experienced Data Engineer to join our data team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, data integration processes, and data infrastructure using Dataiku. You will collaborate closely with data scientists, analysts, and other stakeholders to ensure efficient data flow and support data-driven decision making across the organization. Requirements <ul> <li>8+ years of overall industry experience specifically in data engineering</li> <li>Strong knowledge of data engineering principles, data integration, and data warehousing concepts.</li> <li>Strong understanding of the pharmaceutical/ Life Science domain, including knowledge of patient data, Commercial data, drug development processes, and healthcare data.</li> <li>Proficiency in data engineering technologies and tools, such as SQL, Python, ETL frameworks, data integration platforms, and data warehousing solutions.</li> <li>Experience with data modeling, database design, and data architecture principles.</li> <li>Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms - AWS, Azure</li> <li>Strong analytical and problem-solving skills, with the ability to work with large and complex datasets.</li> <li>Strong communication and collaboration abilities.</li> <li>Attention to detail and a focus on delivering high-quality work.</li> </ul> Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Engineering, Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Snowflake.
Key Responsibilities:
Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements.
Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring.
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable data solutions.
Optimize data pipelines for performance, reliability, and cost-effectiveness, leveraging AWS best practices and cloud-native technologies.
8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
Hands-on experience in designing and building data pipelines
Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
Strong experience with Databricks, Pyspark for data processing and analytics.
Solid understanding of data modeling, database design principles, and SQL and Spark SQL.
Experience with version control systems (e.g., Git) and CI/CD pipelines.
Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
Strong problem-solving skills and attention to detail.
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

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Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world. The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges.We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level. Requirements 8+ years of overall industry experience specifically in data engineering 5+ years of experience building and deploying large-scale data processing pipelines in a production environment. Strong experience in Python, SQL, and PySpark Creating and optimizing complex data processing and data transformation pipelines using python Experience with "Snowflake Cloud Datawarehouse" and DBT tool Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models Strong analytic skills related to working with unstructured datasets Build processes supporting data transformation, data structures, metadata, dependency and workload management Experience supporting and working with cross-functional teams in a dynamic environment Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Engineering, Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Snowflake. Key Responsibilities: <ul> <li>Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.</li> <li>Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements.</li> <li>Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring.</li> <li>Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable data solutions.</li> <li>Optimize data pipelines for performance, reliability, and cost-effectiveness, leveraging AWS best practices and cloud-native technologies.</li> </ul>Requirements <ul> <li>8+ years of experience building and deploying large-scale data processing pipelines in a production environment.</li> <li>Hands-on experience in designing and building data pipelines </li> <li>Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.</li> <li>Strong experience with Databricks, Pyspark for data processing and analytics.</li> <li>Solid understanding of data modeling, database design principles, and SQL and Spark SQL.</li> <li>Experience with version control systems (e.g., Git) and CI/CD pipelines.</li> <li>Excellent communication skills and the ability to collaborate effectively with cross-functional teams.</li> <li>Strong problem-solving skills and attention to detail.</li> </ul> Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

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Data Engineer Tiger Analytics Jobs

Data Engineer AwsDecember 1, 2024

Senior Data EngineerNovember 28, 2024

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