Job Description

We are

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. With top clients to boast about, Synechron has a global workforce of 14,500+, and has 58 offices in 21 countries within key global markets.

Key Responsibilities

Design, develop, and maintain scalable ETL pipelines and frameworks for data ingestion, transformation, and loading.
Utilize UNIX shell scripting and Python for data processing and automation tasks.
Develop and optimize Spark and Spark SQL jobs for large-scale data processing.
Work with SQL, PLSQL, and Teradata for querying and managing data warehouse environments.
Manage job scheduling using Autosys Scheduler to ensure timely data workflows.
Implement and maintain data warehousing solutions, ensuring data integrity and quality.
Collaborate with data scientists, analysts, and other engineering teams to support data requirements.
Leverage AWS services such as S3, EMR, Athena, and other data-related AWS products to enable efficient cloud data lake processing and analytics.

Required Skills and Experience

Strong proficiency in UNIX shell scripting and Python programming.
Practical experience with Apache Spark and Spark SQL.
Solid knowledge of SQL, PLSQL, and Teradata database management.
Hands-on experience designing and managing ETL pipelines and frameworks.
Deep understanding of data warehousing concepts and best practices.
Experience working with Autosys Scheduler or similar job scheduling tools.
Experience with AWS services such as S3, EMR, Athena, and other basic AWS data products.
Ability to troubleshoot and optimize data workflows and pipeline performance.