Data Architect

Key Responsibilities

• Experience in understanding and translating data, analytic requirements and functional needs into technical requirements while working with global customers.
• Design cloud-native data architectures that support scalable, real-time, and batch processing.
• Build and maintain data pipelines to support large scale data management in alignment with data strategy and data processing standards.
• Define strategies for data modeling, data integration, and metadata management.
• Strong experience in database, data warehouse, data lake design & architecture.
• Leverage cloud platforms (AWS, Azure, GCP, etc.) for data storage, compute, and analytics services such as Azure Synapse, AWS Redshift, or Google BigQuery.
• Experience in Database programming using multiple flavour of SQL.
• Implement data governance frameworks, including data quality, lineage, and cataloguing.
• Collaborate with cross-functional teams, including business analysts, data engineers, and DevOps teams.
• Experience in Big Data ecosystem - on-prem (Hortonworks/MapR) or Cloud (Dataproc/EMR/HDInsight/Databricks/SnowPark)
• Evaluate emerging cloud technologies and recommend improvements to data architecture.
• Experience in any orchestration tool such as Airflow/Oozie for scheduling pipelines
• Hands-on experience in using Spark Streaming, Kafka, Databricks, Snowflake, etc.
• Experience working in an Agile/Scrum development process.
• Experience to optimize data systems for cost efficiency, performance, and scalability.

Required Skills and Experience

• Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
• 10+ years of experience in data architecture, data engineering, or related roles.
• 5+ years of experience in building scalable enterprise data warehousing and modelling on prem and/or cloud (AWS, GCP, Azure).
• Expertise in data structures, distributed computing, manipulating and analyzing complex high-volume data from variety of internal and external sources.
• Expertise in cloud platforms such as Azure, AWS, or Google Cloud and their data services (e.g., Azure Data Lake, AWS S3, BigQuery).
• Hands-on experience with data integration tools (e.g., Azure Data Factory, Talend, Informatica).
• Experience in developing ETL designs and data models for structured/ unstructured and streaming data sources
• Experience with real-time data streaming technologies like Kafka,Kinesis, or Event Hub.
• Proficiency with big data tools and frameworks like Apache Spark, Databricks, Snowflake or Hadoop.
• Experience with SQL and NoSQL databases (e.g., SQL Server, Snowflake, Cosmos DB, DynamoDB).
• Solid knowledge of scripting and programming languages such as Python, Spark, Java, or Scala.
• Design secure data solutions ensuring compliance with standards such as GDPR, HIPAA, or CCPA.
• Implement and enforce data governance frameworks, including data cataloguing, lineage, and access controls