Senior Data Architect

About the Role

We are seeking a
Senior Data Architect
with deep
Big Data Engineering expertise
to design and modernize
large-scale, cloud-native data platforms
. This role emphasizes
distributed data processing, real-time pipelines, data platform automation
, and
GenAI enablement
on top of strong Big Data foundations.

Key Responsibilities

• Architect and govern
  enterprise Big Data platforms
  (data lake, lakehouse, warehouse, real-time).
• Design
  high-volume, high-velocity data pipelines
  using batch and streaming frameworks.
• Lead implementation of
  distributed processing architectures
  (Spark, PySpark, EMR).
• Build
  event-driven and real-time streaming solutions
  (Kafka, Kinesis, Flink).
• Define
  ETL/ELT patterns
  , metadata-driven pipelines, and reusable ingestion frameworks.
• Drive
  data platform automation
  (Airflow/Step Functions, CI/CD, data quality, observability).
• Optimize
  performance, scalability, fault tolerance, and cost
  across Big Data workloads.
• Integrate
  GenAI architectures
  (LLMs, embeddings, vector databases, RAG) with enterprise data lakes.
• Ensure
  security, governance, lineage, and compliance
  across data platforms.
• Provide hands-on leadership and technical mentoring to data engineering teams.

Required Technical Skills & Experience

• 12+ years
  in
  Big Data Engineering / Data Architecture
  roles.
• Expert-level experience with
  Spark, PySpark, SQL
  , and distributed compute engines.
• Strong knowledge of
  AWS Big Data stack
  : S3, EMR, Glue, Athena, Redshift, Lambda, Step Functions.
• Hands-on experience with
  Snowflake
  (performance tuning, data sharing, optimization).
• Expertise in
  streaming platforms
  : Kafka, Kinesis, Flink, or Spark Streaming.
• Strong experience with
  data modeling
  (dimensional, Data Vault 2.0).
• Proficiency in
  Python
  , schema evolution, partitioning, and data versioning.
• Experience with
  orchestration and automation
  tools (Airflow, Dagster, CI/CD).
• Working knowledge of
  GenAI data integration
  (feature stores, vector DBs, RAG pipelines).

Experience with
Agile delivery
and leading globally distributed engineering teams