Data Engineer

About the Role

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate will have strong expertise in data modeling, ETL development, cloud platforms, and big data technologies. You will work closely with analytics, engineering, and product teams to ensure reliable, high-quality data availability across the organization.

Key Responsibilities

Design, develop, and maintain ETL/ELT pipelines for batch and streaming data.

Build scalable and high-performance data pipelines, workflows, and integrations.

Develop and optimize data models, data warehouses, and data lakes.

Work with internal stakeholders to understand data requirements and deliver solutions.

Monitor, troubleshoot, and improve data pipeline performance and reliability.

Implement best practices for data quality, governance, and security.

Collaborate with software engineers and analysts for cross-functional data initiatives.

Create and maintain technical documentation.

Required Skills & Experience

Strong experience with SQL and relational databases (PostgreSQL, MySQL, etc.).

Hands-on experience with Python, Java, or Scala for data processing.

Experience with ETL tools/frameworks: Airflow, AWS Glue, DBT, Kafka, Spark, or similar.

Familiarity with cloud platforms: AWS / GCP / Azure.

Experience with data warehousing solutions: Redshift, BigQuery, Snowflake, Databricks, etc.

Understanding of data modeling, schema design, and data architecture.

Experience working with big data technologies (Hadoop ecosystem, Spark, Hive, etc.).

Strong problem-solving and debugging skills.

Knowledge of CI/CD and version control (Git).

Good to Have

Experience with containerization (Docker, Kubernetes).

Familiarity with machine learning pipelines.

Exposure to REST APIs and microservices.

Knowledge of data governance frameworks.