Lead Data Engineer

Celebal Technologies; Dadri, Jaipur, Bengaluru; On-site; INR 3,000,000 - 7,200,000; Full time

Job summary

Celebal Technologies is seeking a Senior Solution Architect to join our Databricks Practice in shaping data modernization journeys for enterprise customers. You will translate business problems into architectural blueprints and guide EDW modernization programs using Lakehouse solutions on the Databricks platform.

Responsibilities include leading pre-sales discussions, designing end-to-end architectures, migrating from legacy systems, and advocating advanced Databricks features.

Qualifications

• 8+ years in data engineering / data platform architecture, with 3+ years hands on on Databricks in a customer-facing or consulting capacity.
• Led at least 2 large- scale EDW modernization or Lakehouse migration programs end to end.
• Strong, fundamentals-level understanding of the Databricks Data Intelligence Platform.
• Delta Lake internals, Spark execution model, and Unity Catalog concepts.

Responsibilities

• Lead pre-sales and delivery architecture conversations with enterprise customers, owning the technical narrative.
• Design end-to-end Databricks Lakehouse architectures across ingestion, transformation, governance, ML, and consumption layers.
• Advise customers on advanced Databricks features and production-grade ETL with Lakeflow.
• Mentor engineers and architects on best practices and governance frameworks.
• Produce client-ready deliverables including HLD/LLD documents and migration roadmaps.

Skills

SQL

PySpark

Stakeholder management

Cloud platforms

Tools

Terraform

Databricks Asset Bundles

MLflow

Delta Lake

Unity Catalog

Job description

Job Summary:

We are seeking a Senior Solution Architect to join our Databricks Practice and play a pivotal role in shaping data modernization journeys for enterprise customers. This is a customer-facing, consulting-oriented role where you will engage with CDOs, Data Architects, and Engineering leaders to design and deliver scalable, future-ready Lakehouse solutions on the Databricks Data Intelligence Platform.

You will be the trusted technical advisor translating business problems into architectural blueprints, guiding customers through EDW modernization programs, and championing the adoption of Databricks' most advanced capabilities including Lakeflow Declarative Pipelines (LDP), Lakeflow Connect, Serverless Compute, Unity Catalog, and AI/BI workloads.

Looking for Immediate Joinees

Responsibilities:

• 1. Lead pre-sales and delivery architecture conversations with enterprise customers, owning the technical narrative from discovery through solution design and through implementation oversight.
• 2. Design end-to-end Databricks Lakehouse architectures spanning ingestion, transformation, governance, ML, and consumption layers aligned to Medallion Architecture principles.
• 3. Drive EDW modernization engagements, including migration strategies from legacy platforms (Teradata, Netezza, Oracle, SAS, Greenplum, Synapse, Snowflake, on-prem Hadoop) to Databricks, with clear wave planning, risk mitigation, and TCO/ROI articulation.
• 4. Advise customers on the adoption of advanced Databricks features.
• 5. Lakeflow Declarative Pipelines (LDP / formerly DLT) for production-grade ETL with built-in data quality and lineage.
• 6. Lakeflow Connect for managed ingestion from SaaS, databases, and file sources.
• 7. Serverless Compute (SQL warehouses, jobs, notebooks) for cost and operational efficiency.
• 8. Unity Catalog for unified governance, lineage, and fine-grained access control.
• 9. Databricks Asset Bundles (DAB) for CI/CD and environment promotion
• 10. Databricks SQL, AI/BI Dashboards, Genie for self-service analytics
• 11. Expertise in Data Bulid Tool (DBT) and Databricks Autoloader
• 12. Databricks SQL, AI/BI Dashboards, Genie for self-service analytics
• 13. MLflow, Model Serving, and Mosaic AI for ML and GenAI workloads
• 14. Conduct architecture deep-dives, PoCs, and workshops including cost modelling roadmaps, runbooks and executive presentations.
• 15. Produce Client ready deliverables. HLD / LLD documents, reference architecture, migration road maps, runbook and execution presentations
• 16. Partner with sales, delivery, and Databricks field teams to shape proposals, SoWs, and bid responses.
• 17. Stay ahead of the Databricks product roadmap and evangelize new capabilities internally and with customers.
• 18. Mentor data engineers, platform engineers, and junior architects on Databricks best practices.

Qualifications

• 8+ years in data engineering / data platform architecture, with 3+ years hands on on Databricks in a customer-facing or consulting capacity.
• Demonstrated experience leading at least 23 large- scale EDW modernization or Lakehouse migration programs end to end.
• Strong, fundamentals-level understanding of the Databricks Data Intelligence Platform.
• Delta Lake internals (transaction log, OPTIMIZE, Z- order, Liquid Clustering, Deletion Vector, Predictive Optimization)
• Spark execution model, Photon, cluster sizing, and performance tuning.
• Unity Catalog object model (metastore, catalogs, schemas, volumes, external locations, stor age credentials).

Workspace, account, and identity architecture across AWS / Azure / GCP.

Handson experience designing and deploying Lakeflow Declarative Pipelines, Lakeflow Conn ect, and Serverless workloads in production.

• Solid grounding in Medallion Architecture, dimensional modeling, and data governance fra meworks.

Strong SQL and PySpark skills; comfort reading and reasoning about Spark execution plans.

• Cloud fluency on at least one of Azure, AWS, or GCP including networking, IAM, and storage layers (ADLS Gen2 / S3 / GCS).
• Excellent communication and stakeholder management skills able to engage equally with engineers and C- suite

Willing to travel and stay overseas for Solutioning and Delivering projects.

Required Skills

• Databricks certifications: Certified Data Engineer Professional, Certified Machine Learning Pr ofessional, or Databricks Certified Solutions Architect Professional.

Experience with DR architectures (Delta Deep Clone, cross region replication, RPO/RTO design).

• Exposure to MLOps / GenAI patterns on Databricks (MLflow, Model Serving, Vector Search, Mosaic AI Agent Framework)
• Familiarity with legacy ETL/ELT platforms (Informatica, ODI, SAS DI, DataStage, Talend) for migration credibility.
• Experience with Terraform / Databricks Asset Bundles for IaC and CI/CD.

Working knowledge of Immuta, Collibra, Purview, or Alation for governance integration.

Industry depth in BFSI, Insurance, Retail, Manufacturing, or Healthcare.

Preferred Skills

Owned the architecture for at least 2 strategic customer engagements from discovery to go live.

Established yourself as the goto advisor on advanced Databricks adoption (LDP, Lakeflow Co nnect, Serverless) within the practice

Contributed to reusable accelerators, reference architectures, and migration playbooks that scale across the practice.

Built strong working relationships with Databricks field teams and contributed to joint pursuits.