Data Engineer
We are seeking a motivated Data Engineer with 2-3 years of experience to join our innovative team. In this role, you will design, build, and optimize data pipelines and analytics workflows using modern data platforms and tools. You will collaborate with cross-functional teams to transform raw data into actionable insights that power intelligent product features and strategic decision-making.
Responsibilities
Design and implement robust data pipelines using PySpark, SQL, and Microsoft Fabric.
Performance tune Stored procedures, UDFs and build indexes required.
Build and maintain data lakehouses and dataflows in Fabric to support scalable data ingestion and transformation
Develop efficient ETL/ELT workflows for structured and semi-structured data from various sources
Optimize query performance and data processing in distributed environments (Spark, Lakehouse, Delta)
Collaborate with analysts and business stakeholders to create impactful Power BI dashboards and reports
Design and implement semantic models and data marts to support self-service analytics
Integrate data from APIs, databases, cloud storage, and third-party sources into a unified analytics platform
Implement data quality checks, monitoring, and alerting systems to ensure data integrity
Document data models, data flows, and technical processes clearly and consistently
Participate in code reviews and contribute to team knowledge sharing and best practices
Stay updated on advancements in data engineering, Microsoft Fabric, and analytics technologies
Requirements
2-3 years of professional experience in data engineering or a related field
Strong proficiency in SQL for data transformation, aggregation, and performance tuning
Hands-on experience with PySpark or similar distributed data processing tools
Practical experience with Microsoft Fabric, including Dataflows, Notebooks, and Lakehouse
Experience in building and maintaining Power BI reports and dashboards
Familiarity with delta tables, parquet, and data lake best practices
Solid understanding of data modeling concepts, including star/snowflake schemas
Experience working with large datasets and optimizing data workflows
Basic knowledge of CI/CD, version control, and collaborative software development
Bachelors degree in Computer Science, Data Engineering, or a related technical field (or equivalent experience)
Preferred Qualifications
Experience integrating with cloud data platforms (e.g., Azure Data Lake, Synapse, AWS S3)
Familiarity with orchestration tools like Azure Data Factory, Apache Airflow, or Fabric Pipelines
Exposure to DataOps, testing frameworks for data, and metadata-driven pipelines
Knowledge of row-level security, data governance, and compliance frameworks
Experience with Python scripting for data wrangling and automation tasks