Data Engineer - PowerBI

Accountabilities:

• • Design, develop, and maintain scalable ETL/ELT pipelines capable of processing large volumes of structured and unstructured data.
  • Build and optimize data warehouse, data lake, and lakehouse solutions to support efficient reporting and analytics.
  • Integrate data from internal and external sources to create unified, reliable, and analysis-ready datasets.
  • Implement data validation, cleansing, transformation, and reconciliation processes to maintain data accuracy, consistency, and completeness.
  • Develop and maintain Power BI dashboards and reports for business and leadership stakeholders.
  • Design optimized Power BI semantic models using star and snowflake schemas, with a focus on scalability and performance.
  • Develop and optimize DAX measures, calculated columns, and KPIs aligned with business metrics.
  • Use Power Query (M) to perform transformations and prepare reliable, refresh-ready reporting datasets.
  • Manage Power BI Service deployments, including scheduled refreshes, workspace access, report sharing, and related administration.
  • Improve report and dashboard performance through optimized data models, relationships, aggregations, and queries.
  • Collaborate with product managers and business stakeholders to understand reporting requirements and translate them into technical deliverables.
  • Provide technical recommendations that improve reporting accuracy, usability, performance, and decision-making.
  • Participate in Agile ceremonies including sprint planning, daily stand-ups, reviews, and related delivery activities.
  • Test pipelines, transformations, semantic models, dashboards, and end-to-end reporting workflows to ensure reliability and correctness.
  • Develop appropriate unit tests and data validations while proactively identifying and resolving defects and performance bottlenecks.
  • Continuously evaluate data engineering and Power BI technologies and recommend improvements to scalability, maintainability, and efficiency.
  • Contribute to modern cloud-based data solutions using platforms such as Azure, AWS, and GCP.

  Requirements:

  • Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
  • At least 3 years of professional experience as a Data Engineer, BI Engineer, or in a closely related data and analytics role.
  • Strong hands-on expertise with Power BI, including semantic data modeling, DAX, Power Query (M), dashboard development, and report optimization.
  • Strong SQL skills, preferably with MySQL or PostgreSQL, including experience with query optimization.
  • Proficiency in Python for data transformation, automation, integrations, and data-processing workflows.
  • Solid understanding of data warehousing, lakehouse principles, data modeling, and performance-tuning concepts.
  • Exposure to modern data technologies such as Databricks, Spark, PySpark, and Pandas.
  • Experience working with APIs and data integrations, including frameworks such as Flask or similar technologies.
  • Familiarity with development and data-engineering utilities such as logging, requests, subprocess, regular expressions, and pytest.
  • Working knowledge of Git and modern collaborative software-development workflows.
  • Comfortable working in Linux environments and writing basic shell scripts.
  • Strong analytical and problem-solving abilities, with excellent attention to detail.
  • Ability to investigate complex data issues and develop reliable, maintainable solutions.
  • Strong communication skills and the ability to collaborate effectively with technical and non-technical stakeholders.
  • Adaptability and willingness to learn new tools, technologies, and data-engineering practices as project requirements evolve.
  • Ability to work effectively in an Agile environment while managing priorities, dependencies, and delivery expectations.

  Benefits:

  • Competitive compensation based on experience, expertise, and skills.
  • Fully remote work arrangement within India.
  • Opportunity to work on impactful data engineering and business intelligence projects.
  • Hands-on exposure to Power BI, modern data platforms, cloud technologies, and data engineering practices.
  • Opportunities to work with technologies including Databricks, Spark, PySpark, Python, SQL, and cloud platforms.
  • Collaborative environment involving data, engineering, product, and business stakeholders.
  • Opportunities for continuous learning and professional development.
  • Exposure to complex data challenges and opportunities to expand technical expertise across data engineering and analytics.
  • Inclusive work environment focused on collaboration, innovation, empowerment, leadership, teamwork, and excellence.