As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data solutions that support reporting, analytics, and business decision-making. You will work with large datasets and modern cloud technologies to build data pipelines, transform and integrate data, and deliver trusted datasets for business intelligence solutions.

The role requires hands-on experience with SQL, Python, data modeling, ETL/ELT development, Azure Synapse Analytics, Microsoft Fabric, Data Factory Pipelines, and Notebooks. You will collaborate with Solution Architects, Business Intelligence teams, and business stakeholders to deliver reliable and efficient data platforms and analytical solutions.

Required Skills and Experience
Exposure to Python programming, especially pandas, basic file handling, data transformations, automation scripts, and reusable functions.
Working knowledge of SQL for querying, joins, aggregations, views, data validation, and performance-aware development.
Basic to intermediate understanding of data engineering concepts such as ETL/ELT, ingestion,



transformation, orchestration, scheduling, and incremental loads.
Exposure to Microsoft Fabric, Azure Synapse, Azure Data Factory, Databricks, or any contemporary cloud data platform. Microsoft Fabric exposure is preferred.
Understanding of data modeling concepts for BI/reporting, preferably dimensional modeling, star schema, fact/dimension tables, and KPI definition logic.
Ability to understand business reporting requirements and translate them into data preparation or model requirements.
Good analytical thinking, troubleshooting ability, and attention to data quality and validation.
Clear communication skills and willingness to document technical work in a structured manner.

Good to Have
Exposure to Power BI semantic models, DAX basics, dataflows, report refresh troubleshooting, or certified datasets.
Understanding of Lakehouse/Warehouse patterns, medallion architecture, Delta tables, Spark note

📌 Data Engineer (Hyderabad)
🏢 Diebold
📍 Hyderabad