Senior Data Architect

About the Role

We are looking for an experienced Senior Data Architect to design and lead scalable, secure, and high-performance data architecture solutions. The ideal candidate should have strong expertise in data modeling, data engineering, cloud data platforms, data governance, and modern data architecture.

You will work closely with engineering, product, business, and leadership teams to define data strategies and architecture that support analytics, reporting, AI/ML, and business applications.

Key Responsibilities

• Design and develop scalable enterprise data architectures aligned with business and technology objectives.
  

• Define data architecture strategies, standards, principles, and roadmaps.
  

• Design data models, data warehouses, data lakes, lakehouse architectures, and data pipelines.
  

• Lead architecture decisions across batch and real-time data processing environments.
  

• Evaluate and recommend appropriate cloud data platforms, databases, and data technologies.
  

• Design and optimize ETL/ELT pipelines for large-scale data processing.
  

• Ensure data solutions are scalable, reliable, secure, and cost-effective.
  

• Establish data governance, data quality, metadata management, lineage, and security standards.
  

• Collaborate with Data Engineers, Data Scientists, BI teams, Software Engineers, and business stakeholders.
  

• Review existing data platforms and identify opportunities for modernization and performance improvement.
  

• Provide technical leadership and mentor data engineering teams.
  

• Define best practices for data integration, storage, processing, and consumption.
  

• Ensure compliance with security, privacy, and regulatory requirements.
  

• Stay updated with emerging technologies in Cloud, Big Data, Data Engineering, AI/ML, and Modern Data Architecture.
  

Required Skills & Experience

• 5+ years of experience in Data Engineering / Data Architecture / Data Platforms.
  

• Strong experience in designing enterprise-scale data architectures.
  

• Excellent knowledge of Data Warehousing, Data Lakes, Lakehouse, ETL/ELT, and Data Modeling.
  

• Strong hands-on experience with SQL and relational/non-relational databases.
  

• Experience with cloud platforms such as AWS, Azure, or GCP.
  

• Experience with modern data technologies such as Databricks, Snowflake, Spark, Kafka, or similar platforms.
  

• Strong understanding of batch and real-time data processing.
  

• Experience designing scalable and high-performance data pipelines.
  

• Knowledge of data governance, security, data quality, metadata, and lineage.
  

• Strong understanding of distributed systems and big data technologies.
  

• Experience with architecture documentation and technical design.
  

• Strong analytical, problem-solving, communication, and stakeholder management skills.
  

Good to Have

• Experience with Databricks / Azure Data Factory / Synapse / Microsoft Fabric / Snowflake.
  

• Experience with Apache Spark, Kafka, Airflow, dbt, or similar technologies.
  

• Exposure to AI/ML data platforms and Generative AI use cases.
  

• Experience with Data Mesh, Data Fabric, or Domain-Driven Data Architecture.
  

• Cloud certifications such as Azure, AWS, or Databricks.
  

• Experience working in Agile/Scrum environments.