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.
Pay: ₹2,000,000.00 - ₹2,500,000.00 per year
Benefits:
Application Question(s):
- What is your total years of experience?
- What is your notice period?
- What is your current CTC?
- What is your expected CTC?
Education:
Experience:
- Python: 4 years (Required)
- PySpark: 4 years (Preferred)
- ApacheSpark: 3 years (Preferred)
Work Location: Remote
