Job description

About the position Responsibilities • Define and maintain the enterprise data architecture blueprint, including data models, integration patterns, and data flows. • Design modern data platforms (data lakes, data warehouses, lake houses) on cloud and/or hybrid environments (Azure, AWS, GCP, Databricks, Snowflake etc.). • Develop data integration architectures for ingestion, processing, storage, and consumption across batch and real-time scenarios. • Ensure data solutions follow principles of security, scalability, cost optimization, and high availability. • Translate business requirements into technical designs and implementation roadmaps. • Lead end-to-end solution architecture for ETL/ELT pipelines, APIs, streaming data, and analytics workloads. • Guide engineering teams in implementing data governance, quality, lineage, and metadata management frameworks. • Select and recommend data technologies, tools, and frameworks based on business priorities and technology roadmaps. • Establish data security and privacy standards aligned with regulatory requirements (GDPR, CCPA, HIPAA, etc.). • Implement data lifecycle management and retention policies. • Ensure architecture adheres to enterprise IT standards and cloud architecture frameworks. • Act as a trusted advisor to business and technical teams for data-related initiatives and projects. • Work with Pre-Sales, Consulting, practice and delivery teams at various stages of life cycle. • Mentor and guide data engineers, analysts, and developers on best practices. • Engage in RFP/RFI processes, providing solution proposals and architecture diagrams. Requirements • 15+ years in data architecture, data engineering, or related roles, with at least 5 years as a Solution Architect and 3 years leading a Data Practice. • Strong expertise in cloud data platforms (Azure Synapse, AWS Redshift, Google BigQuery, Databricks, Snowflake). • Implemented at least 2 – 3 Enterprise Data Lake projects leveraging any of the Industry leading products/vendors (Azure / AWS / Databricks / Snowflake). • Strong expertise in Azure Data Services: Synapse Analytics, Data Lake Gen2, Data Factory, Azure SQL, Event Hub, Cosmos DB. • Experience in Microsoft Fabric: OneLake, Fabric Dataflows, Lakehouse, Fabric Notebooks, Semantic Models. • Proficient in Databricks (Azure/AWS): Lakehouse architecture, Delta Lake, MLflow, Unity Catalog, Spark optimizations. • Expertise in AWS Data Services: S3, Redshift, Glue, Athena, Kinesis, RDS, Lake Formation. • Expertise in ETL/ELT pipelines, batch and streaming architectures. • Strong experience with SQL, Python, PySpark, Scala, and Spark tuning. • Extensive experience in Databricks Lakehouse solutions, Delta lakes, Genie like frameworks. • Deep understanding of IAM, RBAC, data encryption, PII handling, and compliance frameworks (e.g., GDPR, HIPAA). • Familiarity with governance tools: Azure Purview, AWS Glue Catalog, Unity Catalog. Nice-to-haves • Microsoft Certified: Azure Solutions Architect / Data Engineer Associate. • AWS Certified: Solutions Architect – Associate / Big Data Specialty. • Databricks Certified Data Engineer or Architect. • Prior experience with hybrid and multi-cloud data environments. Benefits • Flexible and inclusive work culture. • Opportunities for career growth.

Requirements