About the role
Who are we
Fulcrum Digital is an agile and next-generation digital
accelerating company providing digital transformation and technology services
right from ideation to implementation. These services have applicability across
a variety of industries, including banking & financial services, insurance,
retail, higher education, food, healthcare, and manufacturing.
About the role
We are looking for a Data Engineering Lead with 10-14 years of experience to drive solution architecture, client engagements, pre-sales activities, and technical leadership. The ideal candidate should have deep expertise in Databricks, Apache Pinot, Spark, Kafka, Python, and SQL, along with exceptional communication and stakeholder management skills.
- Participate in pre-sales discussions, solutioning workshops, and client stakeholder meetings.
- Lead client POCs, technical assessments, and architecture discovery sessions.
- Design and implement scalable end-to-end Data & Analytics solutions on Databricks.
- Architect and build batch and real-time data pipelines using Spark, Kafka, and Python.
- Design and implement Lakehouse architectures, Delta Lake, and Medallion frameworks.
- Drive Apache Pinot-based real-time analytics and low-latency data solutions.
- Establish data governance, security, and best practices using Unity Catalog.
- Define and implement CI/CD and DevOps best practices for data platforms.
- Perform architecture reviews, code reviews, performance tuning, and cost optimization.
- Work closely with business stakeholders, delivery teams, and client leadership.
- Mentor and guide Data Engineers and Technical Leads, fostering technical excellence and capability development across the team.
- Provide hands-on technical leadership during design, development, and production support activities.
- Databricks (Expert Level)
- Apache Spark / PySpark
- Python
- SQL
- Apache Kafka
- Apache Pinot
- Delta Lake & Lakehouse Architecture
- Unity Catalog
- CI/CD & DevOps
- Data Modeling & Performance Optimization
- 10-14 years of overall experience in Data Engineering.
- 5+ years of hands-on Databricks experience.
- 3+ years of participating in pre-sales calls/ architecture level discussion.
- Strong experience in client-facing roles, pre-sales, solutioning, and stakeholder management.
- Proven track record in building enterprise-scale data platforms and mentoring technical teams.
- Excellent verbal and written communication skills.
- Strong presentation and stakeholder management abilities.
- Ability to engage confidently with client executives, business leaders, and technical teams.
- Proven leadership and team mentoring experience.
relevant expereince - 5 years to 8 years
RequirementsKey Responsibilities
- Participate in pre-sales discussions, solutioning workshops, and client stakeholder meetings.
- Lead client POCs, technical assessments, and architecture discovery sessions.
- Design and implement scalable end-to-end Data & Analytics solutions on Databricks.
- Architect and build batch and real-time data pipelines using Spark, Kafka, and Python.
- Design and implement Lakehouse architectures, Delta Lake, and Medallion frameworks.
- Drive Apache Pinot-based real-time analytics and low-latency data solutions.
- Establish data governance, security, and best practices using Unity Catalog.
- Define and implement CI/CD and DevOps best practices for data platforms.
- Perform architecture reviews, code reviews, performance tuning, and cost optimization.
- Work closely with business stakeholders, delivery teams, and client leadership.
- Mentor and guide Data Engineers and Technical Leads, fostering technical excellence and capability development across the team.
- Provide hands-on technical leadership during design, development, and production support activities.