Big Data Architect

Minfy Technologies; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Minfy Technologies in Hyderabad, India is seeking an Architect to design and optimize large-scale data platforms using Databricks and Snowflake, driving cost-efficient lakehouse solutions and providing hands-on technical leadership. You will define end-to-end architectures, guide ingestion and compute frameworks, and partner with pre-sales to shape solutions and build convincing POCs.

The role requires 5–8 years of experience with Databricks/Snowflake, cloud data services, and strong

Qualifications

• 5-8 years designing large-scale data platforms.
• 3+ years hands-on with Databricks and/or Snowflake.
• Strong performance tuning, cost optimization, and workload management.
• Experience with cross-functional teams including data engineering, analytics, ML and pre-sales.
• Hands-on with cloud data services (S3/ADLS/GCS, Lambda/Functions, Glue/Synapse/Data Factory, Kubernetes, CI/CD).

Responsibilities

• Define end-to-end architecture for enterprise data platforms across Databricks and Snowflake.
• Design and implement ingestion, transformation, and compute optimization using Spark, SQL, Delta Lake.
• Develop standards for data modeling, data quality, medallion architecture, and orchestration.
• Partner with pre-sales and solutioning teams to qualify use cases, shape architecture, estimate workloads, and build POCs.
• Evaluate new capabilities; drive platform modernization, automation, observability, and best-practice adoption.

Skills

Databricks architecture depth

Data modeling & lakehouse

Cloud ecosystems (AWS/Azure/GCP)

Communication to stakeholders

SQL, Python, Spark performance tuning

Tools

Databricks

Snowflake

Spark

Delta Live Tables

Unity Catalog

Job description

Architect, design, and optimize large-scale data platforms using Databricks, Snowflake, and modern lakehouse patterns. Provide deep hands-on technical leadership while partnering with pre-sales teams to shape scalable, cost-efficient solutions. Build proofs-of-concept as an individual contributor to validate architectures and demonstrate value.

Responsibilities

• Define end-to-end architecture for enterprise data platforms across Databricks, Snowflake, and cloud ecosystems, ensuring scalability, performance, governance, and security.
• Design and implement ingestion, transformation, and compute optimization frameworks using Spark, SQL, Delta Lake, and platform-native capabilities, balancing cost and performance.
• Develop standards for data modeling, data quality, medallion architecture, and workload orchestration, collaborating closely with data engineering, analytics, and ML teams.
• Partner with pre-sales and solutioning teams to qualify use cases, shape solution architecture, estimate workload sizing, and build compelling POCs showcasing technical feasibility.
• Evaluate new capabilities in Databricks, Snowflake, and cloud services; drive platform modernization, automation, observability, and best-practice adoption across teams.

Knowledge & Skills

• Expert-level knowledge of Databricks (Spark, Delta Live Tables, Unity Catalog) and/or Snowflake (Warehouses, Query Optimization, Snowpark), with strong architectural depth.
• Strong grounding in data modeling, data warehousing, data governance, lakehouse patterns, and distributed systems concepts.
• Understanding of cloud ecosystems (AWS/Azure/GCP), including storage systems, IAM, networking, orchestration, and CI/CD for data pipelines.
• Ability to articulate complex architectural concepts to technical and business stakeholders, connecting platform capabilities to business outcomes.
• Advanced SQL, Python, and Spark programming skills with ability to optimize distributed workloads, troubleshoot cluster performance, and tune compute resources.

Mandatory Experience

• 5-8 years of experience designing and delivering large-scale data platform architectures, including at least 3 years hands-on in Databricks and/or Snowflake.
• Demonstrated experience building POCs, reference implementations, and end-to-end solutions as an individual contributor with deep technical ownership.
• Strong background in performance tuning, cost optimization, cluster sizing, query optimization, and workload management on modern data platforms.
• Experience working with cross-functional teams including data engineering, analytics, ML, and pre-sales/sales solutioning functions.
• Hands-on experience with cloud data services (e.g., S3/ADLS/GCS, Lambda/Functions, Glue/Synapse/Data Factory, Kubernetes, CI/CD).