Job highlights

- Experience working with clients and managing conflicts
- . Mentor and provide guidance to junior data engineers and team members. What we look for: . 4+ years experience in data engineering,data architecture,data platforms analytics
- . At least 3+ years experience with Databricks,PySpark,Python,and SQL
- Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to s and productionalizing customer use cases.
- Work with engagement managers to scope variety of professional services work with input from the customer.
- Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications.
- Consult on architecture and design, bootstrap or implement customer projects which leads to a customers successful understanding, evaluation and adoption of Databricks.
- Support customer operational issues with an escalated level of support.
- Ensure that the technical components of the engagement are delivered to meet customer s needs by working with the Project Manager, Architect, and Customer teams.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions.
- Mentor and provide guidance to junior data engineers and team members.

What we look for:





- 4+ years experience in data engineering, data architecture, data platforms analytics.
- At least 3+ years experience with Databricks, PySpark, Python, and SQL.
- Consulting / customer facing experience, working with external clients across a variety of industry markets.
- Comfortable writing code in both Python and SQL.
- Proficiency in SQL and experience with data warehousing solutions.
- Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
- Strong understanding of data modeling, ETL processes, and data architecture principles.
- Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments GitHub, Azure DevOps, Azure Pipelines.
- Working knowledge of MLOps methodologies.
- Design and deployment of performant end-to-end data architectures.
- Experience with technical project delivery managing scope and timelines.
- Documentation and white-boarding skills.
- Experience working with clients and managing conflicts.
- Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
- Good to have Databricks Certifications.
- Solid communication and collaboration skills.
- Excellent problem-solving skills.

📌 Senior Data Engineer (Hyderabad)
🏢 DataNimbus
📍 Hyderabad