Company: MyExecutiVeera

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Startup

Company Type: Product & Service

Business Model: B2B

Funding Stage: Pre-seed

Industry: Information Technology & Services

KEY RESPONSIBILITIES

- Serve as a lead engineer and trusted technical advisor on customer Databricks engagements, from design through production deployment
- Deliver hands-on development on Databricks across multiple customer projects
- Design and optimize distributed-computing workloads on Spark, applying knowledge of Spark runtime internals
- Implement CI/CD for production deployments
- Operationalize MLOps workflows to support machine-learning use cases
- Advise on and apply the breadth of Databricks product and platform features
- Tune workloads for performance, scalability, and cost efficiency
- Work across two or more cloud ecosystems (AWS, Azure, GCP), applying deep expertise in at least one
- Guide customers through best-practice lakehouse implementation and production readiness
- Collaborate with customer stakeholders and onshore leads overlapping PST hours to ensure timely, high-quality delivery

Required Qualifications & Skills

- 6–10 years of experience in data engineering, data platforms, and analytics, including substantial consulting experience.
- Completed the Databricks Data Engineering Professional certification and the required Databricks classes.
- Minimum 6–8+ projects delivered with hands-on development experience on Databricks.




- Working knowledge of two or more common cloud ecosystems (AWS, Azure, GCP), with deep expertise in at least one.
- Deep experience with distributed computing on Spark, including knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments.
- Working knowledge of MLOps.
- Current knowledge across the breadth of Databricks product and platform features.
- Familiarity with optimizations for performance and scalability.
- Excellent communication and customer-facing skills, with the ability to work across time zones.
- Bachelor's/Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).

Mandatory Skills

- Hands-on development experience on Databricks (6–8+ projects)
- Databricks Data Engineering Professional certification (+ required classes)
- Distributed computing on Spark, incl. Spark runtime internals
- Two or more cloud ecosystems (AWS / Azure / GCP), deep in at least one
- CI/CD for production deployments
- MLOps (working knowledge)
- Breadth of Databricks product & platform features
- Performance & scalability optimization

Nice To Have Skills

- PySpark / Python and robust SQL
- Delta Lake, Unity Catalog, and Delta Sharing
- Streaming data pipelines (Spark Streaming / Kafka)
- Prior consulting or field-engineering experience with an ISV or platform vendor

CLOUD PLATFORMS & SERVICES AWS, Azure, and GCP working knowledge of two or more cloud ecosystems is required, with deep expertise in at least one.

📌 Lead Data Engineer (Bengaluru)
🏢 Sourcingxpress
📍 Bengaluru