Position Overview : The role requires close collaboration with business stakeholders, data analysts, product teams, and technology teams to ensure high-quality, reliable, and secure data solutions.

Key Responsibilities

Data Engineering & Development

- Design, build, and maintain robust ETL/ELT pipelines for ingesting data from multiple sources, including:

- Develop and optimize data models, data warehouses, and data marts.

- Implement batch and real-time data processing solutions.

- Ensure data quality, integrity, consistency, and availability across enterprise systems.

- Create reusable frameworks for data ingestion, transformation, validation, and monitoring.

Data Platform & Architecture

- Build scalable cloud-based data platforms and lakehouse architectures.
- Manage structured, semi-structured, and unstructured datasets.
- Implement data governance, metadata management, and lineage tracking.
- Support master data management initiatives.

Analytics & Reporting

- Collaborate with CRM and other teams to deliver datasets for various Business Insight Analytics - Sales analytics, Policy conversion analytics Customer acquisition and retention analytics, Renewal analytics, Claims analytics, Cross-sell and upsell performance tracking
- Optimize datasets for reporting and dashboarding requirements.

Performance & Reliability

- Monitor data pipeline performance and troubleshoot production issues.
- Implement automated testing, alerting, and monitoring mechanisms.
- Ensure compliance with SLAs for data availability and processing timelines.

Security & Compliance

- Ensure adherence to data privacy and security regulations.
- Implement access controls, encryption, and secure data handling practices.
- Support audit and compliance requirements relevant to the insurance industry.

Primary Skills (required)





- Strong SQL skills and database optimization experience.
- Strong and demonstrable Data Modelling experience
- Proficiency in Python, PySpark, Scala, or Java.
- Experience with ETL/ELT development and orchestration tools.
- Experience working with cloud platforms (preferably AWS)
- Experience with data warehouse technologies such as (PostgreSQL or Snowflake or BigQuery)
- Knowledge of distributed data processing frameworks (PySpark or Apache Spark or Hadoop etc.)
- Experience with workflow orchestration tools: (AWS Glue or Airflow)
- Experience with version control systems such as Git.
- Experience with Unix/Linux scripting

Secondary Skills (preferred)

- Experience in Insurance, InsurTech, Insurance Broking, Aggregator, or Financial Services domains.
- Understanding of Key Insurance Business Processes & Metrics
- Experience integrating with insurer APIs and third-party data providers.
- Familiarity with DataOps and CI/CD practices.
- Knowledge of streaming technologies such as Kafka

Qualifications :

- Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent practical experience).
- 6-8 years of extensive professional experience working as a data & visualization engineer.
- Excellent problem-solving, debugging, and analytical skills.
- Robust communication and collaboration skills to work effectively in a team environment.
- Ability to work in a fast-paced, data-driven environment and write clean, maintainable, and well-documented code.
- Strong attention to detail and commitment to data quality.

Pay: ₹800,000.00 - ₹1,000,000.00 per year

Benefits :

- Health insurance
- Leave encashment
- Paid sick time
- Paid time off
- Provident Fund

Education :

- Bachelor's (preferred)

Experience :

- working as a data & visualization engineer.: 6 years (preferred)

Work Location: In person

📌 Data-analytics Engineer (Kolkata)
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