Senior Data Engineer - Hive/Spark

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About The Role

Key Responsibilities

• Design, develop, and maintain reliable and scalable ETL/ELT pipelines and data workflows.
• Build and optimize data warehouses, data lakes, and real-time streaming systems.
• Collaborate with data scientists, analysts, and product teams to ensure high-quality data availability.
• Ensure data accuracy, consistency, and security across different systems.
• Implement data modeling, partitioning, and performance optimization strategies.
• Work with large-scale structured and unstructured data across multiple sources.
• Automate data integration processes and enable self-service analytics.
• Stay updated with emerging data engineering tools, cloud services, and best practices.
  

Required Skills & Experience

• 4 - 8 years of experience as a Data Engineer / Big Data Engineer.
• Strong proficiency in SQL, Python, and/or Scala for data processing.
• Hands-on experience with ETL/ELT tools (Airflow, DBT, Informatica, Talend, or similar).
• Expertise in Big Data technologies : Spark, Hadoop, Hive, Kafka, etc.
• Experience with cloud platforms (AWS, Azure, GCP) and services like Redshift, BigQuery, Snowflake, or Databricks.
• Solid understanding of data modeling, schema design, and data warehousing concepts.
• Familiarity with CI/CD, DevOps practices, and containerization (Docker, Kubernetes) is a plus.
• Excellent problem-solving and communication skills.
  

Good To Have

• Exposure to real-time data streaming and event-driven architectures.
• Experience with data governance, security, and compliance.
• Knowledge of machine learning pipelines and supporting AI/ML teams with data.
  

Why Join Us ?

• Opportunity to work on cutting-edge data platforms and technologies.
• Collaborative and innovative environment.
• Competitive compensation and career growth opportunities.