Sr. Data Engineer

• Create and maintain optimal Data Lake setup.
• Assemble large and complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.

1. Experience with Data Analytics services like EMR, Glue, Athena, Kinesis, MSK, Elasticsearch, Quicksight and Redshift.
2. Experience with Data lake setup and Data warehouse on AWS/GCP.
3. Experience with big data tools: Hadoop, Spark, Kafka, Hive etc.
4. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
5. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
6. Experience with stream-processing systems: Storm, Spark-Streaming, etc.
7. Experience with object-oriented/object function scripting languages: Python, Scala, etc

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