Data Engineer

The Data Engineer will be responsible for designing, building, and maintaining secure, scalable data pipelines and analytics platforms. The role combines data engineering
, analytics enablement
, and AI integration
, leveraging relational databases,
Google Big Query
, modern BI tools, and Python-based machine learning libraries. The ideal candidate will enable data-driven decision-making by ensuring high-quality data ingestion, transformation, analytics, and visualization across the organization.

• Design, build, and maintain secure data ingestion pipelines from multiple internal and external data sources.
• Implement ETL/ELT processes to move and transform data into Google Big Query
  .
• Ensure data quality, validation, lineage, and governance across pipelines.
• Optimize data pipelines for performance, scalability, and cost efficiency.

• Design and manage relational databases using PostgreSQL or MySQL
  .
• Model data for analytics and reporting (star/snowflake schemas).
• Develop and optimize Big Query datasets, tables, partitions, and views.
• Manage data access controls and security policies.

• Enable and support analytics and reporting using Power BI Pro (
  with Copilot
  ) and Looker Enterprise
  .
• Build semantic models, datasets, and data sources for BI tools.
• Collaborate with stakeholders to define KPIs, metrics, and dashboards.
• Ensure performance, reliability, and accuracy of reports and dashboards.
• Develop custom data visualizations using Chart.js and D3.js
  .
• Integrate visualizations into web applications and internal portals.
• Ensure visual clarity, usability, and data accuracy.
• Develop data processing and feature engineering pipelines using Python
  .
• Build and evaluate machine learning models using Scikit-learn and XGBoost
  .
• Perform data analysis and manipulation using Pandas.
• Integrate external AI services such as OpenAI APIs into data workflows and applications.
• Support experimentation, model deployment, and performance monitoring.

• Implement secure data access, encryption, and compliance best practices.
• Monitor data pipelines, troubleshoot failures, and optimize reliability. Technical Skills
  • Minimum 3 years of experience as a Data Engineer.
  • Strong experience with:
    • PostgreSQL or MySQL
    • Google Big Query
    • Secure data ingestion from multiple data sources
    • Python for data engineering and analytics
    • Power BI Pro (Copilot) and Looker Enterprise
  • Hands‑on experience with:
    • Data modeling and warehousing concepts
    • SQL performance tuning and optimization
    • BI semantic layers and dashboards
    • API‑based data ingestion and integration (including OpenAI API
      )
  Soft Skills
  • Strong analytical and problem‑solving skills.
  • Ability to translate business requirements into data solutions.
  • Good communication and documentation abilities.
  • Ability to work in cross‑functional, agile teams.
  Senior level

  Mid‑Senior level

  Employment type

  Full‑time

  Job function

  Administrative and Engineering

  Industries

  Software Development