Data Engineer

We are looking for a skilled Data Engineer to design, build, and optimize scalable data systems that power analytics, reporting, and business intelligence.

You will work closely with software engineers, analysts, and stakeholders to transform raw data into reliable, production-ready datasets and dashboards.

Key Responsibilities

Data Pipeline & ETL Development

• Design, build, and maintain scalable data pipelines

• Develop ETL/ELT processes for structured and unstructured data

• Automate workflows for ingestion and transformation

• Ensure reliability and performance of processing jobs

Database & Data Modeling

• Design optimized storage and warehouse schemas

• Build logical and physical data models

• Integrate multiple data sources into unified datasets

Data Quality & Testing

• Implement validation checks and monitoring

• Troubleshoot inconsistencies and anomalies

• Maintain accuracy, integrity, and availability of data

Business Intelligence & Power BI

• Develop production-ready datasets for reporting

• Build and maintain Power BI semantic models

• Create reusable measures and calculated columns

• Optimize model performance and refresh behavior

• Support reporting and analytics requirements

Architecture & Deployment

• Participate in data architecture planning

• Support CI/CD and data infrastructure deployments

• Monitor pipeline and dataset performance

Security & Compliance

• Implement governance, access control, and privacy safeguards

Documentation & Collaboration

• Document data flows, schemas, and transformations

• Communicate data health and performance to stakeholders

• Collaborate with cross-functional teams

Agile & Continuous Improvement

• Participate in sprint ceremonies

• Propose architecture and workflow improvements

• Contribute to reviews and knowledge sharing

Qualifications (Required)

• Bachelor’s degree in Computer Science, IT, Engineering, or related field

• 2–4+ years Data Engineering experience

• Strong SQL and data transformation skills

• Experience working with large datasets

• Experience with big data environments

• Hands-on Power BI development experience (not reporting only)

Technical Requirements

Applicants must have hands-on experience in several of the following:

Data Engineering

• Python / Advanced SQL

• ETL/ELT pipelines

• Data modeling & warehousing

• Medallion architecture (Bronze–Silver–Gold)

• Apache Spark, Airflow, DBT, or Kafka

• Cloud platforms (AWS / Azure / GCP)

• Data quality monitoring & validation

• CI/CD or DevOps exposure

Power BI (Required)

• DAX measures & calculated columns

• Power Query (M)

• Semantic model design

• Dataset optimization & performance tuning

• Incremental refresh / partitioning concepts

Nice to Have

• Experience supporting analytics or ML pipelines

• Experience working with analysts and BI teams