The Big Data Engineering team is responsible for building and maintaining the state-of-the-art ETL pipelines that makes this data available and accessible to the entire company to make data driven decisions. The team works closely with Data scientists, Product Managers, Executives and other key parts of the business across the globe to understand their data requirements and build appropriate solutions or platforms that meet or exceed those needs.
Contributing at a senior-level to the Big data and data warehouse design and data preparation by implementing a solid, robust, extensible design that supports key business flows.
Performing all of the necessary data transformations to populate data into a warehouse table structure that is optimized for reporting.
Establishing efficient design and programming patterns for engineers as well as for non-technical individuals
Designing, integrating and documenting technical components for seamless data extraction and analysis on our big data platform.
Ensuring best practices that can be adopted in Big Data stack and share across teams and BUs.
Working in a team environment, interacting with multiple groups on a daily basis (very strong communication skills).
Desired skills and experience
2+ years of relevant work experience in data
Ability to write, analyze, and debug SQL queries
Working experience with Hadoop projects/infrastructure
Experience in the Big Data space (Hadoop Stack like Spark, HDFS, Pig, Hive, etc.)
Experience in deploying Big data workloads on Hadoop infrastructure
Experience with Data Warehouse design, ETL (Extract, Transform, Load), architecting efficient software solutions
Knowledge of data modeling for both data warehousing and Big Data
Experience working extensively in multi-petabyte data environment
Experience in engineering large-scale distributed systems in a production environment
Experience with at least one scripting language (Shell, Python, Perl etc.) is must
Experience with an OO programming language like Java a bon
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