Data Analyst, IRS MBI Clearance
Job Description:
• This is a remote position.
• Lead and mentor junior engineers in data pipeline projects.
• Build and optimize ETL/ELT pipelines using various tools.
• Work with SQL, Python or Scala, and data warehouses and lakes.
• Familiarize with cloud platforms, containerization, and CI/CD processes.
Requirements:
• NEED IRS MBI Clearance.
• Experience & Leadership: 3–5+ years in data engineering or backend data systems, with experience leading data pipeline projects and mentoring junior engineers.
• Data Pipeline Expertise: Proficient in building and optimizing ETL/ELT pipelines using tools like Apache Airflow, Spark, dbt, Kafka, Databricks, or Flink.
• Tech Stack & Tools: Strong skills in SQL, Python or Scala, and working with data warehouses (Snowflake, BigQuery, Redshift) and data lakes (e.g., Delta Lake, Lakehouse architecture).
• Infrastructure & Ops: Familiar with cloud platforms (AWS, GCP, Azure), containerization (Docker/Kubernetes), and orchestration, with experience in CI/CD and data versioning (e.g., DVC).
• Bonus/Preferred: Experience with real-time data processing, cataloging, data governance, privacy/compliance (GDPR, HIPAA), and cross-functional collaboration with analytics, ML, or BI teams.
Benefits:
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• This is a remote position.
• Lead and mentor junior engineers in data pipeline projects.
• Build and optimize ETL/ELT pipelines using various tools.
• Work with SQL, Python or Scala, and data warehouses and lakes.
• Familiarize with cloud platforms, containerization, and CI/CD processes.
Requirements:
• NEED IRS MBI Clearance.
• Experience & Leadership: 3–5+ years in data engineering or backend data systems, with experience leading data pipeline projects and mentoring junior engineers.
• Data Pipeline Expertise: Proficient in building and optimizing ETL/ELT pipelines using tools like Apache Airflow, Spark, dbt, Kafka, Databricks, or Flink.
• Tech Stack & Tools: Strong skills in SQL, Python or Scala, and working with data warehouses (Snowflake, BigQuery, Redshift) and data lakes (e.g., Delta Lake, Lakehouse architecture).
• Infrastructure & Ops: Familiar with cloud platforms (AWS, GCP, Azure), containerization (Docker/Kubernetes), and orchestration, with experience in CI/CD and data versioning (e.g., DVC).
• Bonus/Preferred: Experience with real-time data processing, cataloging, data governance, privacy/compliance (GDPR, HIPAA), and cross-functional collaboration with analytics, ML, or BI teams.
Benefits:
Apply tot his job
Apply To this Job