Data Pipeline Architect

3 days ago

Kottayam, Kerala, India beBeeDataEngineering Full time ₹ 1,20,00,000 - ₹ 2,00,00,000

Job Title: Data Engineering Professional

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  • ">
  • Job Description">

The role of a Data Engineer is to design, build, and maintain large-scale data systems that support business operations. This includes developing and deploying data pipelines, implementing data warehouses and lakes, and ensuring data quality and integrity.

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As a Data Engineer, you will work closely with cross-functional teams to understand business requirements and develop solutions that meet those needs. You will be responsible for building and maintaining data pipelines, working with cloud-based services such as GCP and AWS, and using tools like Python, PySpark, and GenAI to automate tasks and improve efficiency.

">Required Skills and Qualifications">
  • ">
  • Strong proficiency in Python and PySpark">
  • Working experience with cloud platforms like GCP and/or AWS">
  • Solid understanding of ETL/ELT, data warehouse and data lake concepts">
  • Proficient in working with relational databases—preferably PostgreSQL and MySQL—as well as non-relational databases, with a focus on MongoDB">
  • Driven by delivery and results — you get things done efficiently">
  • Self-starter attitude with minimal need for hand-holding">
  • Excitement for automating work using GenAI or scripting tools">
  • Familiarity with SCD, CDC, Real-time Streaming vs Batch-processing">
">Benefits">

This role offers a high-impact opportunity where execution speed is valued and recognized. You will have the freedom to build, ship, and iterate without red tape, working with a lean, high-performing data team. Opportunities to innovate with Generative AI tools are also available.

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Fast learning environment and ownership from day one make this an ideal role for someone who prefers delivering over deliberating.

">

Key Responsibilities

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  • ">
  • Build, deploy, and manage data pipelines using Python and PySpark">
  • Develop and optimize ETL/ELT processes to support data integration across systems">
  • Work directly with GCP and AWS services to implement scalable cloud-based data solutions">
  • Own data workflows end-to-end — from ingestion to transformation to storage">
  • Continuously monitor and improve pipeline reliability, speed, and data quality">
  • Use GenAI and automation tools to speed up development and reduce manual effort">
  • Proactively debug, troubleshoot, and resolve data engineering issues">
  • Ensure data is available and trustworthy for analytics and downstream systems">
  • Deliver high-quality code and documentation with a bias for action">
  • Nice to Have: Experience with CI/CD pipelines and Docker, Understanding of data governance and observability, Prior experience in fast-paced, execution-heavy teams">
"]],

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