Senior Data Engineer

Senior Data Engineer

Key Responsibilities

Data Engineering & Pipelines

• Design, develop, and maintain scalable

  data pipelines

  using cloud-native services (GCP/AWS/Azure).
• Build

  ETL/ELT workflows

  for structured and unstructured data.
• Implement

  batch and real-time data ingestion

  using tools like Kafka / PubSub / Kinesis.
• Automate data workflows using

  Airflow / Composer / Azure Data Factory

  .

Data Modelling & Warehousing

• Design

  data models

  (dimensional/normalized) for analytics and reporting.
• Manage and optimize

  data warehouses

  such as BigQuery, Snowflake, Redshift, Azure Synapse.
• Implement best practices for

  partitioning, clustering, and performance tuning

  .

Coding & Framework Development

• Write clean, efficient code in

  Python / Scala / Java

  .
• Build reusable data engineering frameworks and libraries.
  
• Develop

  unit tests, CI/CD pipelines

  , and ensure code quality.

Cloud & Infrastructure

• Hands-on experience with

  Cloud Storage, Compute, Containers (Docker/Kubernetes)

  .
• Monitor systems using logging, alerting, and observability tools.
  
• Ensure

  security, cost optimization, and reliability

  of data infrastructure.

Collaboration & Leadership

• Work closely with Data Scientists, Analysts, and Product Teams.
  
• Mentor junior engineers and guide best engineering practices.
  
• Participate in architecture discussions and contribute to technical roadmaps.
  

Required Skills & Experience

Must Have

• 6+ years experience in

  Data Engineering

  .
• Strong hands-on skills in

  Python

  (or Scala/Java).
• Expert in

  SQL

  and query performance tuning.
• Experience with

  cloud platforms

  (GCP / AWS / Azure).
• ETL/ELT pipeline development with

  Airflow / Composer / ADF / Step Functions

  .
• Experience with

  Big Data

  tools (Spark / Dataproc / EMR / Databricks).
• Stream processing experience using

  Kafka / PubSub / Kinesis

  .
• Strong knowledge of

  data modelling

  (Star schema, SCD, Fact/Dimension).

Good to Have

• Cloud certifications (GCP Professional Data Engineer / AWS Data Analytics).
  
• Experience with

  Docker/Kubernetes

  .
• Familiarity with BI tools (Looker, Tableau, Power BI).
  
• Experience with

  ML pipelines

  (Kubeflow, Vertex AI, SageMaker).