Data Architect

4 weeks ago

Delhi, 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 postgreSQL, 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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