Data Engineer

About The Role The role is responsible for designing, building, and maintaining robust data pipelines and infrastructure that power both core business analytics and production machine learning models. This position collaborates closely with analytics engineers, product managers, and downstream data consumers to ensure the reliability, quality, and latency standards of a rapidly expanding data warehouse. Key Responsibilities Design and implement scalable, robust ETL/ELT pipelines using PySpark, SQL, and DBT to ingest high-volume transactional and clickstream data Maintain and optimize the core cloud data warehouse architecture on Snowflake, managing performance tuning, cost control, and schema design Orchestrate complex, multi-stage data workflows using Apache Airflow, implementing automated testing, data quality validation, and alert systems Collaborate with software engineering teams to define and implement event schemas and logging standards for new feature launches Develop and enforce data governance policies, including access control, data lineage tracking, and compliance with data privacy regulations Build custom integrations and internal tooling in Python to ingest data from third-party APIs and SaaS tools into the central data lake What We Are Looking For 3–6 years of experience in data engineering, backend software engineering, or a highly technical analytics role Expert‑level SQL proficiency and strong programming skills in Python or Scala for complex data processing Hands‑on experience with modern cloud data warehouses (Snowflake, BigQuery, or Redshift) and data lake architectures Proven experience with workflow orchestration tools (Apache Airflow, Prefect, or Dagster) and data transformation frameworks like DBT Solid understanding of data modeling concepts, including dimensional modeling (Kimball methodology) and data vault design BS/MS in Computer Science, Engineering, Information Systems, or a related quantitative field Bonus: Experience with streaming data technologies (Kafka, Kinesis, Flink), Kubernetes, or infrastructure‑as‑code tools like Terraform #J-18808-Ljbffr