Maintain, update, and expand existing core data platform pipelines.
Build and maintain APIs to expose data to downstream applications.
Work with technologies including Airflow, Spark, Databricks, Delta Lake, and Snowflake.
Collaborate with product managers, architects, and other engineers to ensure platform success.
Develop and document internal/external standards, best practices, and pipeline configurations.
Ensure high operational efficiency and data accuracy to meet SLAs and reliability standards for stakeholders (Engineering, Data Science, Operations, and Analytics teams).
Required Qualifications:
7+ years of data engineering experience developing large-scale data pipelines.
Proficiency in at least one major programming language (Python, Java, or Scala).
Hands‑on experience with distributed processing systems such as Apache Spark.
Production‑level experience with data pipeline orchestration tools like Apache Airflow.
Expertise in at least one Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, BigQuery).
Experience in data modeling and API development using GraphQL.
Advanced understanding of OLTP vs. OLAP environments.