Data Product Engineering Specialist

2 weeks ago


Gurgaon, Haryana, India BLJ Tech Geeks Full time

Responsibilities :

  • Design, build, and maintain scalable data products to support analytics, AI/ML, and operational business needs.
  • Develop high-quality data pipelines and reusable configurable frameworks, ensuring robust, efficient, and scalable data processing.
  • Implement data transformation and enrichment processes to make raw data useful for pricing, risk modeling, claims, and other business functions.
  • Ensure adherence to data modeling standards, reference data alignment, and data product governance frameworks.
  • Work closely with Product Managers, Designers, and Domain SMEs to embed best practices and standards.
  • Leverage cloud-based technologies and modern data platforms focusing on Azure data services and Databricks.
  • Ensure solutions align with data security, privacy, and governance policies.
  • Engage with platform teams to ensure efficient deployment and performance optimization of data solutions.
  • Develop automated test routines and conduct thorough testing to ensure quality deliverables.
  • Integrate solutions with data management tools such as Purview to automate data quality rules implementation, metadata management, and tagging.
  • Develop clean and precise documentation, inc. low-level designs, release notes, and how-to guides.
  • Support Data product launch and adoption activities.
  • Keep up to date with new skills - Develop technology skills in other areas of Platform.
  • Stay updated on emerging data technologies and continuously enhance data products to improve efficiency and business value.
  • Optimize data processing performance and cost-efficiency by leveraging automation and modern engineering best practices.
  • Identify opportunities for AI/ML integration and automation within data pipelines and business processes.
Requirements :
  • Advanced understanding of building and deploying production-grade solutions in complex projects.
  • Strong experience in data engineering, data modeling, and pipeline development.
  • Proficiency in SQL, Python, Spark, Databricks, and cloud-based data engineering tools (Azure preferred, AWS, GCP).
  • Strong experience in software engineering practices and implementation.
  • Experience with big data processing, streaming architectures (Kafka, Event Hub), and real-time data solutions.
  • Understanding of data governance, metadata management, and data lineage frameworks.
  • Knowledge of CI/CD practices, DevOps, and Infrastructure as Code (IaC) for data solutions.
  • Knowledge of using advanced tools and techniques to identify and address data quality issues.
  • Strong stakeholder management, able to influence and drive alignment across cross-functional teams.
  • Excellent problem-solving and analytical skills with a product mindset.
  • Ability to work in agile environments, contributing to product roadmaps and iterative development cycles.
(ref:hirist.tech)

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