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Job Description & How to Apply Below
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Job Summary:
We are seeking a skilled and motivated Data Engineer to join our growing team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines and infrastructure on the On-Premises and cloud platform. You will leverage your expertise in PySpark, Spark, Python and Apache Airflow to process and orchestrate large-scale data workloads, ensuring data quality, efficiency, and scalability.
If you have a passion for data engineering and a desire to make a significant impact, we encourage you to apply!
Key Responsibilities:
Data Engineering & Data Pipeline Development
Design, develop, and optimize scalable DATA workflows using Python, PySpark, and Airflow
Implement real-time and batch data processing using Spark
Enforce best practices for data quality, governance, and security throughout the data lifecycle
Ensure data availability, reliability and performance through monitoring and automation.
Cloud Data Engineering :
Manage cloud infrastructure and cost optimization for data processing workloads
Implement CI/CD pipelines for data workflows to ensure smooth and reliable deployments.
Big Data & Analytics:
Build and optimize large-scale data processing pipelines using Apache Spark and Py Spark
Implement data partitioning, caching, and performance tuning for Spark-based workloads.
Work with diverse data formats (structured and unstructured) to support advanced analytics and machine learning initiatives.
Workflow Orchestration (Airflow)
Design and maintain DAGs (Directed Acyclic Graphs) in Airflow to automate complex data workflows
Monitor, troubleshoot, and optimize job execution and dependencies
Required Skills & Experience :
4+ years of experience in data engineering with expertise in PySpark, Spark.
Strong programming skills in Python, SQL with the ability to write efficient and maintainable code
Deep understanding of Spark internals (RDDs, Data Frames, DAG execution, partitioning, etc.)
Experience with Airflow DAGs, scheduling, and dependency management
Knowledge of Git, Docker, Kubernetes, and apply best practices of Dev Ops for CI/CD workflows
Experience in cloud platform like Azure/AWS is favourable.
Excellent problem-solving skills and ability to optimize large-scale data processing.
Experience in Agile/Scrum environments
Strong communication and collaboration skills, with the ability to effectively work with remote teams
Bonus Points:
Experience with data modeling and data warehousing concepts
Familiarity with data visualization tools and techniques
Knowledge of machine learning algorithms and frameworks
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