Databricks Solution Architect

Codvo.ai; Pune District; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

A leading data solutions company in Pune is seeking a skilled Databricks Solution Architect to design and implement complex data architectures. The ideal candidate will have over 8 years of experience with a strong focus on Databricks, cloud services, and data engineering. Responsibilities include leading architectural decisions, collaborating with cross-functional teams, and mentoring junior staff. This role offers a chance to work on innovative data solutions while impacting business outcomes positively.

Qualifications

• 8+ years of experience in solutions/enterprise architecture or senior data engineering roles.
• 3+ years hands-on experience with the Databricks platform and Spark-based architectures.
• Strong cloud experience with AWS, Azure, or GCP.

Responsibilities

• Lead design and delivery of analytics solutions on the Databricks platform.
• Engage with business stakeholders to translate needs into solutions.
• Design data lakehouse architectures that support governance and analytics.

Skills

Solutions/enterprise architecture

Databricks platform

Data engineering

Cloud services (AWS/Azure/GCP)

Advanced SQL

Python/Scala programming

Communication skills

Stakeholder management

Education

Bachelor's degree in relevant field

Tools

Apache Airflow

Kafka

Databricks SQL

Delta Lake

Job description

Job Title: Databricks Solution Architect

Experience: 10+ years

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.

Senior / Expert Databricks Solutions Architect — Job Description

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.