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.

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 - Robust
- Python
- SQL - Strong
- 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
- Solid 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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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