Data Architect

Geodis India Pvt.Ltd; Ernakulam; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Geodis India Pvt.Ltd seeks an experienced Data Architect with 7+ years to lead the design and evolution of our enterprise data platform, focusing on Cloudera, Databricks, data lakehouse architecture, governance, and data products.

You will define modern data patterns, guide engineering teams, design scalable solutions, and ensure secure data sharing across internal analytics and external clients, aligning with business goals.

Qualifications

• 7+ years of experience in data engineering, data architecture, data warehousing, big data, or enterprise data platforms.
• Strong hands‑on experience with Cloudera Data Platform or equivalent big data ecosystem.
• Strong experience with Databricks, Spark, or similar platforms.
• Strong SQL and data modeling skills.
• Experience designing batch, streaming, and near-real-time data pipelines.
• Experience with cloud storage such as ADLS, S3, or equivalent.
• Ability to produce architecture diagrams and technical design documents.

Responsibilities

• Define and maintain enterprise data architecture standards, patterns, and reference architectures.
• Design scalable data lake, data warehouse, and lakehouse solutions using Cloudera, Databricks, ADLS, Spark, Kafka, Starburst.
• Lead architecture decisions for batch, streaming, real-time data processing.
• Establish best practices for data ingestion, transformation, storage, access, and data sharing.
• Design architecture for internal analytics and external client data sharing.

Skills

Cloudera

Databricks

Data Lakehouse

Data Modeling

Data Governance

Kafka

SQL

Cloud Data Platform

Streaming Architecture

Data Integration

Education

Bachelor's degree in Computer Science, Data Engineering or related field

Tools

Cloudera Data Platform

Databricks

Spark

NiFi

Kudu

Unity Catalog

ADLS

Job description

Summary:

We are seeking an experienced Data Architect with 7+ years of experience to lead the design and evolution of our enterprise data platform, with strong hands-on expertise in Cloudera, Databricks, data lakehouse architecture, data governance, data integration, and enterprise data products.

This role will be responsible for defining modern data architecture patterns, designing scalable data solutions, enabling secure and governed data sharing, and guiding engineering teams in building reliable, reusable, and business-aligned data products.

The ideal candidate will have deep experience across data platforms, cloud data ecosystems, streaming architecture, data modeling, data governance, and enterprise integration patterns.

Job Duties:

Primary Duties:

Enterprise Data Architecture

• Define and maintain enterprise data architecture standards, patterns, and reference architectures.
• Design scalable data lake, data warehouse, and lakehouse solutions using Cloudera, Databricks, ADLS, Spark, Kafka, Starburst, and related technologies.
• Lead architecture decisions for batch, streaming, real-time, and near-real-time data processing.
• Establish best practices for data ingestion, transformation, storage, access, consumption, and data sharing.
• Design architecture for internal analytics, external client data sharing, operational reporting, and data monetization use cases.

Cloudera & Databricks Solution Design

• Architect solutions on Cloudera Data Platform, including Kudu, Spark, NiFi, and security components.
• Architect solutions on Databricks, including Unity Catalog, Databricks Workflows, notebooks, SQL Warehouses, and data sharing capabilities.
• Define migration and coexistence patterns between on-prem data warehouse, Cloudera, Databricks, and cloud storage.
• Design integration patterns between Databricks and external platforms such as Snowflake, Power BI, Qlik, APIs, and middleware systems.
• Guide teams on performance optimization, partitioning, file formats, data layout, cluster sizing, and cost optimization.

Data Modeling & Data Product Design

• Lead conceptual, logical, and physical data modeling for enterprise data domains.
• Define reusable data product patterns aligned to business domains and consumption needs.
• Design curated, trusted, and governed data layers such as bronze, silver, and gold.
• Establish source-to-target mapping standards, transformation rules, and semantic layer principles.
• Collaborate with business stakeholders to convert business requirements into scalable data solutions.

Data Governance, Security & Compliance

• Define architecture for data governance, metadata management, data lineage, access control, and data classification.
• Implement governance patterns using tools such as Unity Catalog, DataHub, or similar technologies.
• Define data access models for internal teams, external clients, and third‑party platforms.
• Ensure compliance with enterprise security standards, privacy requirements, and audit controls.
• Establish standards for encryption, masking, row‑level security, column‑level security, and secure data sharing.

Data Integration & Streaming Architecture

• Design integration patterns for application databases, APIs, files, CDC, middleware, and streaming platforms.
• Define Kafka-based ingestion and event‑driven architecture patterns.
• Support data movement from on‑prem databases such as Oracle, SQL Server, PostgreSQL, and MySQL into modern data platforms.
• Design resilient pipelines with retry, error handling, reconciliation, observability, and operational support.
• Partner with application, middleware, infrastructure, and cloud teams to deliver end‑to‑end data solutions.

Technical Leadership

• Provide architectural guidance to data engineers, platform engineers, DBAs, and application teams.
• Review solution designs, data models, pipeline designs, and implementation approaches.
• Create architecture diagrams, design documents, standards, patterns, and technical roadmaps.
• Lead proof-of-concepts, platform evaluations, and migration planning.
• Mentor junior and mid-level engineers on modern data engineering and architecture practices.

Requirements:

Education and Experience:

• Bachelors degree in Computer Science, Data Engineering or related field from a 4 year college or university.
• 7+ years of experience in data engineering, data architecture, data warehousing, big data, or enterprise data platforms.
• Strong hands‑on experience with Cloudera Data Platform or equivalent big data ecosystem.
• Strong experience with Databricks, Spark, or similar platforms.
• Strong SQL and data modeling skills.
• Experience designing batch, streaming, and near-real-time data pipelines.
• Experience with relational databases such as Oracle, PostgreSQL, SQL Server, or MySQL.
• Experience with cloud or object storage such as ADLS, S3, or equivalent.
• Strong understanding of data governance, metadata, lineage, access control, and security patterns.
• Experience with Kafka or event streaming platforms.
• Experience designing enterprise-grade data platforms with high availability, scalability, reliability, and performance.
• Ability to produce architecture diagrams, technical design documents, standards, and executive-level architecture presentations.

Preferred Skills:

• Experience with Snowflake, Power BI, Qlik, Tableau, or data API platforms.
• Experience with DataHub, Apache Atlas, Unity Catalog, or similar governance tools.
• Experience with CDC tools, API‑based ingestion, middleware integration, and file‑based data exchange.
• Experience with data monetization, client‑facing data products, or external data sharing.
• Experience migrating from legacy on‑prem data warehouses to modern date lake platforms.
• Experience with DevOps, CI/CD, Git, Terraform, Ansible, or automated deployment of data pipelines.
• Experience with monitoring and observability for data pipelines and platforms.

Certifications Preferred:

• Databricks Data Engineer Associate or Professional.
• Databricks Lakehouse Fundamentals.
• Cloudera Data Platform certification.
• Data governance or architecture certifications preferred.