Data Engineer

About the Role

We are looking for a passionate Data Engineer with 4+ years of experience in designing, developing, and maintaining scalable data platforms and ETL/ELT pipelines. The ideal candidate should possess strong expertise in Python, SQL, cloud data services, and modern data engineering frameworks. You will play a key role in building reliable, high-performance data solutions that support analytics, reporting, and AI/ML initiatives.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.

• Build and optimize data ingestion processes from multiple structured and unstructured data sources.

• Develop robust data models and data warehouses for analytics and reporting.

• Design and optimize SQL queries for high-performance data processing.

• Build and maintain data lakes using cloud storage solutions.

• Implement data validation, cleansing, transformation, and quality checks.

• Integrate data solutions with cloud platforms such as AWS, Azure, or Google Cloud Platform.

• Develop batch and real-time data processing pipelines using modern data processing frameworks.

• Collaborate with data scientists, analysts, and application teams to deliver reliable data solutions.

• Follow software engineering best practices, including Git, CI/CD pipelines, testing, monitoring, and technical documentation.

Required Skills

• 4+ years of experience in Data Engineering.

• Strong programming experience in Python.

• Hands-on experience with PySpark and Apache Spark.

• Advanced SQL skills, including query optimization and performance tuning.

• Experience with AWS services/ Azure/ GCP.

• Experience building scalable ETL/ELT pipelines.

• Strong experience in Generative AI and Large Language Models (LLMs)

• Knowledge of data warehousing concepts and dimensional modeling.

• Experience working with large-scale distributed datasets.

• Familiarity with Git and CI/CD pipelines.

• Understanding Agile/Scrum methodologies.

Preferred Qualifications

• Experience with Apache Airflow or similar workflow orchestration tools.

• Knowledge of Kafka and real-time data streaming.

• Familiarity with Docker, Kubernetes, and Terraform (IaC).

• Exposure to Databricks and modern data lake technologies (Delta Lake, Apache Iceberg, or Apache Hudi).

• Understanding data governance, metadata management, and CI/CD practices.

• Strong experience in Generative AI and Large Language Models (LLMs)

• Strong analytical, problem-solving, and communication skills.

Qualifications

• Bachelor's degree in computer science, Information Technology, Engineering, or related technical discipline.