Senior Data Engineer
Senior Data Engineer building ETL pipelines, data processing systems, and Lakehouse architecture on AWS to map decision-maker networks. Requires 6+ years experience, expert SQL, Spark, and data warehousing tools.
Senior Data Engineer
Designs and owns data architecture, builds/optimizes pipelines and models using Python, SQL, Snowflake, dbt, and AWS. Manages SLAs, data governance, and mentors team; requires 5+ years experience and bachelor's in CS or related.
160k – 220kNew York, NYData EngineeringOnsite5+ YOE
About the role
Responsibilities
- Collaborate with cross-functional teams to develop end-to-end data pipelines and foundational data sets
- Design and own data architecture for large-scale projects while managing operational trade-offs
- Build and optimize sophisticated data pipelines, models, and visualizations across multiple domains
- Define and manage Service Level Agreements (SLAs) for all owned data sets
- Implement data security models, ensure privacy compliance, and evolve data governance processes
- Solve complex integration challenges using optimal ETL/ELT patterns for structured and unstructured data
- Maintain production processes by optimizing complex code using advanced algorithmic concepts
- Streamline data artifact development by optimizing pipelines, dashboards, and frameworks
- Mentor team members through actionable feedback to foster collective skill growth
- Maintain flexibility with availability during evening hours
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field (Master's preferred)
- 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
- 5+ years with Python, building scalable Big Data solutions and ETL ecosystems
- Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt
- Hands-on experience with RDBMS such as MySQL, MS SQL Server (optional), and Postgres
- Familiarity with integration tools like Airflow and Automic, along with working knowledge of CI/CD pipelines
- Ability to deliver high standards of code quality, system reliability, and performance
- Deep understanding of modern IaC ecosystem for automated infrastructure deployments
- Experience with cloud computing services, preferably AWS, including Glue, Airflow (MWAA), DMS, EKS, and SNS
Nice-to-haves
- Experience with Spark and PySpark
- Master's degree in Computer Science, Computer Engineering, or relevant field
Compensation
- Base salary: $160,000 - $220,000 USD annually
- Total compensation may include healthcare, 401(k), disability coverage, life insurance, stock options, bonuses
Skills
PythonSQLSnowflakedbtAirflowAWSETLELTPostgresMySQLSparkPysparkGlueCI/CDIac
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