Data Engineer
24 hours ago
Role & responsibilities
- Design, develop, and deploy end-to-end BI and analytics solutions using Power BI, Tableau, and cloud platforms.
- Build visually compelling dashboards and reports with strong data storytelling skills.
- Develop and maintain ETL/ELT pipelines using Azure Data Factory, Databricks, AWS tools, and PySpark.
- Work on data modeling, semantic layers, and optimizing warehouse performance.
- Integrate and analyze data using Big Data technologies such as Spark, Hadoop, Hive, etc.
- Collaborate closely with business teams to convert requirements into actionable insights.
- Ensure data quality, validation, documentation, and governance compliance.
- Manage deployments, versioning, and production issue resolution.
- Evaluate and adopt emerging tools in BI, cloud, and Big Data for continuous improvement.
Preferred candidate profile
We understand that no one has experience in every tool or platform listed below. If you have a strong foundation and any combination of these skills, wed love to hear from you.
Key Skill Areas
ETL / Data Engineering
- Azure Data Factory (ADF)
- dbt
- Data Pipelines (ETL/ELT)
- SQL (Complex queries, optimization)
- Python, PySpark
- Databricks
- AWS Glue, Athena
- Big Data Tools (Hadoop, Spark, Hive, etc.)
Data Warehousing / Storage
- Snowflake
- Azure Synapse
- Azure SQL
- AWS Redshift
- Microsoft Fabric
Data Visualization / BI
- Power BI (Advanced Dashboarding, DAX, Data Modeling)
- Tableau (Visualization & Storytelling)
- QlikView (optional, nice-to-have)
Data Governance & Security
- Understanding of Data Governance, Security & Compliance
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