Databricks Solution Architect (India)

Codvo Private Limited

Pune District

On-site

INR 1,800,000 - 2,500,000

Full time

14 days+

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Job summary

A leading technology firm is seeking a Senior / Expert Databricks Solutions Architect based in India, Maharashtra, Pune District. The role involves leading the design and delivery of data solutions on the Databricks platform, collaborating with various teams, and mentoring junior staff. Candidates should have extensive experience in solutions architecture and the Databricks ecosystem, alongside strong communication and stakeholder management skills. This is an exciting opportunity to drive innovation in data platforms and analytics.

Qualifications

  • 8+ years in solutions/enterprise architecture or senior data engineering roles.
  • 3+ years of hands-on experience with Databricks and Spark architectures.
  • Proven ability to manage complex technical concepts for various audiences.

Responsibilities

  • Design scalable data lakehouse architectures on Databricks.
  • Lead technical architecture decisions and produce high-quality artifacts.
  • Mentor junior architects and engineers.

Skills

Databricks expertise
Cloud services (AWS, Azure, GCP)
Data integration tools (Apache Airflow, Kafka)
SQL and programming (Python, Scala)
Strong communication skills

Education

Relevant certifications (Databricks)

Tools

Databricks platform
MLflow

Job description

Senior / Expert Databricks Solutions Architect — Job Description
About Us

At Codvo, we are committed to building scalable, future‑ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting‑edge technology.

About the role

We are seeking a highly experienced Solutions Architect to lead the design and delivery of end‑to‑end data and analytics solutions on the Databricks platform. You will translate complex business needs into scalable, secure, and cost‑efficient data lakehouse architectures, collaborate with cross‑functional teams, and guide customers from concept through implementation and adoption.

What you’ll do (Responsibilities)
  • Engage with business stakeholders to understand goals, data sources, and analytic use cases; translate into a holistic Databricks‑based solution.
  • Design scalable data lakehouse architectures on Databricks (Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables) that support data ingestion, cleansing, modeling, governance, security, and analytics.
  • Lead technical architecture decisions and produce high‑quality artifacts (reference architectures, solution blueprints, data models, data governance models, and integration plans).
  • Architect data pipelines end‑to‑end (ingestion, transformation, storage, cataloging) with best practices for reliability, observability, and cost optimization.
  • Enable data science and ML workflows on Databricks (MLflow, feature store, notebooks, Automated ML) and design end‑to‑end MLOps strategies.
  • Ensure data governance, security, and compliance (IAM, encryption, Unity Catalog, data masking, lineage, access controls).
  • Collaborate closely with data engineers, data scientists, software engineers, and DevOps to deliver production‑ready solutions; implement CI/CD for data and ML pipelines.
  • Lead customer‑facing activities: workshops, solution demos, proofs of concept, and responses to RFPs/RFIs; provide strategic guidance on platform adoption and ROI.
  • Mentor and coach junior architects and engineers; develop training materials and run knowledge‑sharing sessions.
  • Monitor performance, optimize SQL and Spark workloads, manage cluster configurations, and drive cost/performance improvements.
What you’ll bring (Required qualifications)
  • 8+ years of experience in solutions/enterprise architecture or senior data engineering roles; 3+ years of hands‑on experience with the Databricks platform and Spark-based architectures.
  • Deep expertise in Databricks components: Delta Lake, Unity Catalog, Databricks SQL, Delta Live Tables, notebooks, and orchestration patterns.
  • Strong cloud experience (AWS, Azure, or GCP) with data storage and compute services (e.g., S3/Blob, ADLS, GCS, Redshift, BigQuery, Synapse, EMR/Databricks on cloud).
  • Proficiency in data integration and orchestration tools (e.g., Apache Airflow, dbt, Kafka, Spark Structured Streaming).
  • Advanced SQL and programming skills (Python or Scala); ability to prototype and review data pipelines, models, and analytics solutions.
  • Excellent communication and stakeholder management skills; ability to present complex technical concepts to both technical and non‑technical audiences.
  • Experience delivering large‑scale data lakehouse migrations/transformations, performance tuning, and cost optimization.
  • Databricks certification(s) or equivalent demonstrable expertise; willingness to obtain relevant certifications if not already held.
Preferred qualifications
  • Experience with ML and MLOps on Databricks (MLflow, feature stores, model registry, CI/CD for ML).
  • Domain expertise in industries such as financial services, healthcare, retail, or telecommunications.
  • Familiarity with data governance, privacy regulations, and security frameworks (e.g., GDPR, HIPAA, SOC 2).
  • Familiarity with real‑time data processing and streaming architectures.
  • Prior experience in pre‑sales or solutioning for customers, including building compelling ROI stories and technical demos.
About you (soft skills and capabilities)
  • Strategic thinker with a hands‑on mindset; comfortable operating at both business and technical levels.
  • Strong analytical, problem‑solving, and decision‑making capabilities.
  • Collaborative team player who can lead without authority and influence stakeholders.
  • Comfortable working in a fast‑paced, client‑facing environment with travel as needed.
  • Submit your resume/CV and a brief cover letter outlining your Databricks projects and impact.
  • Include links to relevant work (e.g., public case studies, GitHub repositories, or portfolio demos) if available.
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