Data Engineer

Must have skill set: Java, Scala, S3, Glue, Redshift , AWS

6-8 years of IT experience focusing on enterprise data architecture and management.

• Experience in Conceptual/Logical/Physical Data Modeling & expertise in Relational and Dimensional Data Modeling

• Experience with Databricks & on Prem , Structured Streaming, Delta Lake concepts, and Delta Live Tables required

• Experience with Spark scala and java programming

• Data Lake concepts such as time travel and schema evolution and optimization

• Structured Streaming and Delta Live Tables with Databricks a bonus

• Experience leading and architecting enterprise-wide initiatives specifically system integration, data migration, transformation, data warehouse build, data mart build, and data lakes implementation / support

• Advanced level understanding of streaming data pipelines and how they differ from batch systems

• Formalize concepts of how to handle late data, defining windows, and data freshness

• Advanced understanding of ETL and ELT and ETL/ELT tools such as Data Migration Service etc

• Understanding of concepts and implementation strategies for different incremental data loads such as tumbling window, sliding window, high watermark, etc.

• Familiarity and/or expertise with Great Expectations or other data quality/data validation frameworks a bonus

• Familiarity with concepts such as late data, defining windows, and how window definitions impact data freshness

• Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design performance optimization)

• Indexing and partitioning strategy experience

• Debug, troubleshoot, design and implement solutions to complex technical issues

• Experience working with AWS Lambdas for configuration and optimization and experience with S3

• Familiarity with Schema Registry, message formats such as Avro, ORC, etc.

• Ability to thrive in a team-based environment

• Experience briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior level of management