Data Architect

Requirements

• Assessments of existing data components, Performing POCs, Consulting to the stakeholders
• Proposing end to end solutions to an enterprise's data specific business problems, and taking care of data collection, extraction, integration, cleansing, enriching and data visualization
• Ability to design large data platforms to enable Data Engineers, Analysts & scientistsStrong exposure to different Data architectures, data lake & data warehouse
• Define tools & technologies to develop automated data pipelines, write ETL processes, develop dashboard & report and create insights
• Continually reassess current state for alignment with architecture goals, best practices and business needsDB modeling, deciding best data storage, creating data flow diagrams, maintaining related documentation
• Taking care of performance, reliability, reusability, resilience, scalability, security, privacy & data governance while designing a data architecture
• Apply or recommend best practices in architecture, coding, API integration, CI/CD pipelines
• Coordinate with data scientists, analysts, and other stakeholders for data-related needs
• Help the Practice grow by mentoring junior Practice members, leading initiatives, leading Data OfferingsProvide thought leadership by representing the Practice / Organization on internal / external platforms

Responsibilities

• Translate business requirements into data requests, reports and dashboards.
• Strong Database & modeling concepts with exposure to SQL & NoSQL Databases
• Strong data architecture patterns & principles, ability to design secure & scalable data lakes, data warehouse, data hubs, and other event-driven architectures
• Expertise in designing and writing ETL processes in Python / Java / Scala
• Understanding of Hadoop framework - Exposure to PySpark, Spark, Storm, HDFS, Hive
• Strong hands-on experience with either Databricks or Snowflake; experience with both is desirable.
• Knowledge of Master Data management and related tools
• Strong exposure to data security and privacy regulations (GDPR, HIPAA) and best practices
• Skilled in ensuring data accuracy, consistency, and quality
• Experience with the AWS/Azure/GCP data engineering services
• Knowledge of AWS services viz., AWS S3, Redshift, Lambda, DynamoDB, EMR, Glue, Lakeformation, Athena, Quicksight, RDS, Kinesis, Managed Kafka, API Gateway, CloudWatch
• And / OR
• Knowledge of Azure services viz., ADF, Data Catalog, Databricks, Azure Synapse Analytics, ADLS Gen2, Azure Devops
• Ability to implement data validation processes and establish data quality standards.
• Experience in Linux
• Proficiency in data visualization tools like Tableau, Power BI or similar to create meaningful insights

Desired

• Experience working with data ingestion tools such as Fivetran, stitch, or Matillion
• AWS IOT solutions
• Apache NiFi, Talend, Informatica
• Exposure to AI / ML technologies