Data architect

2 weeks ago


New Delhi, India R Systems Full time

Job Title : Data Engineering Architect Experience : 10-16 Years Location : Pune & Noida Work Mode : Hybrid - Full time Key Responsibilities • Data Migration & Modernization • Lead the migration of data pipelines, models, and workloads in Redshift. • Design and implement landing, staging, and curated data zones to support scalable ingestion and consumption patterns. • Evaluate and recommend tools and frameworks for migration, including file formats, ingestion tools, and orchestration. • Design and build robust ETL/ELT pipelines using Python, SQL, and orchestration tools • Support both batch and streaming pipelines, with real-time processing via rudderstack, or Spark Structured Streaming. • Build modular, reusable, and testable pipeline components that handle high volume and ensure data integrity. • Define and implement data modeling strategies (star, snowflake, normalization/demoralization) for analytics and BI layers. • Implement strategies for data versioning, late-arriving data, and slowly changing dimensions. • Implement automated data validation and anomaly detection (using tools like dbt tests, Great Expectations, or custom checks). • Build logging and alerting into pipelines to monitor SLA adherence, data freshness, and pipeline health. • Contribute to data governance initiatives including metadata tracking, data lineage, and access control. Required Skills & Experience • 10+ years in data engineering roles with increasing responsibility. • Proven experience leading data migration or re-platforming projects. • Strong command of Python, SQL for data pipeline development. • Experience working with dbt models. • Hands-on experience with modern data platforms like postgre SQL, Redshift. • Proficient in building streaming pipelines with tools like Kafka, rudderstack. • Deep understanding of data modeling, partitioning, indexing, and query optimization. • Expertise with Apache airflow for ETL orchestration. • Comfortable working with large datasets and solving performance bottlenecks and optimizing table structures. • Experience in designing data validation frameworks and implementing DQ rules. • Strong understanding of git hub and code migration techniques. • Familiarity with reporting tools like tableau, power bi. • Knowledge of financial domain. Preferably loans


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