Data Engineer - Databricks
$110,000–$160,000 year
On-siteMcLean, Virginia, United States
Job Summary
Lead and architect data pipelines and ingest patterns to move raw data from producers to an enterprise ecosystem, prioritizing performance and reliability. Assess ETL jobs, workflows, BI tools, and reports while addressing technical inquiries regarding customization, integration, and enterprise architecture. Craft database and data warehouse solutions in cloud environments, specifically AWS, utilizing Python, SQL, and Databricks to manipulate, process, and extract value from large, disconnected datasets. Re-implement existing pipelines efficiently within an Agile software development lifecycle. Support the growth of the Data Exploitation Practice by delivering enterprise-grade data platforms and services to clients in the Homeland, Federal Civilian, Health, and DoD sectors.
Required Qualifications
- Ability to hold a position of public trust with the US government
- Bachelor's Degree
- 6+ years of total experience
- 6+ years direct experience in Data Engineering
- Experience with Big data tools: Hadoop, Spark, Kafka, etc
- Relational SQL and NoSQL databases, including Postgres and Cassandra
- Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc
- AWS cloud services: EC2, S3, RDS, Glue, Step Functions, Lamda, EMR, DynamoDB, DocumentDB, Redshift, Aurora, Athena
- Data Platforms: Databricks, Snowflake
- Data streaming systems: Kafka, Storm, Spark-Streaming, etc
- Languages: Python, R, Scala, Go
- Ability to inspect existing data pipelines, discern their purpose and functionality, and re-implement them efficiently in Databricks
- Advanced working SQL knowledge
- Experience working with relational databases
- Advanced working knowledge of NoSQL databases
- Experience with message queuing, stream processing, and highly scalable 'big data' data stores
- Experience manipulating, processing, and extracting value from large, disconnected datasets
- Experience manipulating structured and unstructured data for analysis
- Experience with data modeling tools and processes
- Experience aggregating and transforming data from multiple datasets to create data products
- Experience working in an Agile environment
Desired Qualifications
- Experience in crafting database / data warehouse solutions in cloud (Preferably AWS. Alternatively Azure, GCP)
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