Senior Data Engineer

The Senior Data Engineer

is responsible for designing, building, and maintaining the data pipelines, transformation layers, and data models that power the enterprise lakehouse . This role is a technical anchor on the data engineering team, delivering robust ELT/ETL solutions and serving as a mentor to junior engineers.

KEY RESPONSIBILITIES

Design and implement scalable batch and streaming data pipelines using Apache Spark, Kafka, and Flink

Build and maintain the Bronze/Silver/Gold medallion architecture within the lakehouse (Delta Lake / Iceberg)

Develop and optimize complex SQL and PySpark transformations for large-scale datasets

Integrate structured, semi-structured, and unstructured data sources into the lakehouse

Collaborate with data architects to evolve the physical and logical data models

Implement data quality checks and monitoring using Great Expectations or dbt tests

Write Infrastructure-as-Code for pipeline environments (Terraform, Helm)

Participate in code reviews and enforce engineering standards and best practices

Troubleshoot pipeline failures, performance bottlenecks, and data incidents

Mentor junior and mid-level data engineers and contribute to internal knowledge sharing

REQUIRED QUALIFICATIONS

6 + years of data engineering experience with a track record of enterprise-scale delivery

Expert proficiency in Python and SQL; PySpark experience required

Hands -on experience with Apache Spark, Delta Lake, or Apache Iceberg

Experience with orchestration tools: Apache Airflow, Prefect, or Dagster

Strong knowledge of cloud data services: AWS Glue, Azure Data Factory, GCP Dataflow

Proficiency with version control (Git), CI/CD pipelines, and containerization (Docker/Kubernetes)

Experience with dbt (data build tool) for transformation layer management

Bachelor's degree in Computer Science, Engineering, or related technical field

**PREFERRED QUA