We are looking for an experienced Senior Data Engineer / Senior Data Architect to design, build, and maintain scalable data solutions using Databricks.

The ideal candidate should have strong hands-on experience in Databricks, PySpark, Python, SQL, Delta Lake, ETL/ELT, and Data Modeling. The candidate will work closely with business and technical stakeholders to understand requirements, design data solutions, build reliable data pipelines, and deliver high-quality datasets for reporting, dashboards, and analytics.

This role requires a combination of hands-on Data Engineering, Data Architecture, Data Modeling, Solution Design, and Stakeholder Management skills.

n

Key Responsibilities:

Data Engineering & • Pipeline Development

- Design, develop, and maintain scalable data pipelines using Databricks, PySpark, Python, and SQL.
- Build ETL/ELT pipelines to ingest data from internal and external source systems.
- Load and manage data in Databricks Delta Tables.
- Handle data from multiple and evolving source systems.
- Implement data validation, quality checks, error handling, and monitoring.
- Troubleshoot and optimize data pipelines for performance, reliability, and scalability.

Data Transformation & • Modeling

- Analyze source data and business requirements to design appropriate data transformations.
- Develop standardized and curated datasets for reporting, dashboards, and analytics.

- Design and maintain logical and physical data models.
- Apply dimensional modeling concepts such as fact and dimension tables, star schema, and normalization/denormalization.
- Ensure data models are scalable and aligned with business requirements.

Solution Architecture

- Design end-to-end data architectures and data movement strategies.
- Evaluate source systems and integration patterns and recommend appropriate solutions.

- Design scalable, secure, maintainable, and reliable data solutions.
- Create technical documentation covering architecture, data flows, mappings,



and integration processes.
- Contribute to reusable data engineering frameworks and best practices.

Business & • Stakeholder Management

- Work directly with business users, data consumers, and technical teams to understand and clarify requirements.
- Translate business requirements into technical specifications and data models.
- Understand business processes and determine appropriate data transformation and architecture approaches.
- Communicate technical solutions effectively to both technical and non-technical stakeholders.

Data Governance & • Quality

- Implement data quality and validation frameworks.
- Follow data governance, naming conventions, taxonomy, metadata, and lineage standards.
- Ensure data accuracy, consistency, traceability, and auditability.
- Support enterprise data management and governance initiatives.

Key Skills – Must Have:

- Databricks – Strong hands-on experience
- PySpark – Strong
- Python
- SQL – Robust
- Delta Lake / Delta Tables
- ETL / ELT
- Data Engineering
- Data Modeling
- Data Architecture / Solution Design
- Data Pipeline Development
- Data Transformation and Integration
- Performance Tuning and Optimization
- Data Quality and Validation
- Strong analytical and problem-solving skills
- Strong stakeholder communication skills

Good-to-Have Skills

- AWS / Azure
- Azure Data Factory / AWS Glue
- Power BI / Tableau
- Kafka / Streaming
- CI/CD and DevOps
- Git / Azure DevOps
- Databricks Unity Catalog
- Data Governance
- Metadata and Data Lineage
- Data Taxonomy
- Enterprise Data Standards

Experience:

- 8+ years of overall IT experience
- Strong recent hands-on experience in Databricks and PySpark
- Experience working on enterprise-scale data engineering projects
- Experience designing end-to-end data solutions
- Experience interacting directly with business and technical stakeholders

Work Details:Work Location: Hyderabad

Work Mode: Hybrid – 3 days per week from office

Working Hours: 2:00PM to 11:00 PM.

Role Type: Contract

n

📌 Senior Data Engineer / Senior Data Architect (Hyderabad)
🏢 Trackmind
📍 Hyderabad