Job Description
Hiring for my IT services client - Bengaluru or Noida Location.
Role Overview
As a Data Engineering Architect, you will be the technical guru responsible for designing, building, and scaling our enterprise data ecosystems. You will bridge the gap between complex business requirements and cutting-edge technical solutions. In this role, you will lead the architectural blueprinting for large-scale data migrations, real-time analytics platforms, and robust data governance frameworks tailored for highly regulated industries.
Key Responsibilities
Architectural Leadership:
Design and implement end-to-end data architectures (Data Lakes, Data Warehouses, Lakehouses) using cloud-native technologies (AWS, Azure, or GCP).
Strategy & Roadmap:
Define the data strategy, including tool selection, integration patterns, and long-term scalability plans for global clients.
Execution & Delivery:
Lead engineering teams through the full SDLC, ensuring high-quality code, optimized ETL/ELT pipelines, and rigorous testing standards.
Client Engagement:
Act as a subject matter expert (SME) in client workshops, translating business needs into technical specifications and managing stakeholder expectations.
Mentorship:
Provide technical guidance and career mentorship to senior and mid-level data engineers.
Technical Competencies
CategorySkills & ToolsCloud Platforms AWS (Glue, Redshift, EMR), Azure (Synapse, ADF, Databricks), or GCP (BigQuery, Dataflow).
Data Processing Apache Spark, PySpark, Python, Scala, Kafka, Flink.
Data Modeling Medallion Architecture, Star/Snowflake Schema, Data Vault 2.0.
Storage & Warehousing Snowflake, Databricks, Delta Lake, NoSQL (MongoDB, Cassandra).
DevOps & Governance
CI/CD (Jenkins, GitLab), Terraform/CloudFormation, Great Expectations, Collibra.
Qualifications
Education:
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Experience:
10+ years in Data Engineering, with at least 3 years in a dedicated Architect role within an IT services/consulting context.
Certification:
Professional certifications in Cloud Architecture (e.g., AWS Solutions Architect, Azure Data Engineer Associate) are highly preferred.
Domain expertise:
Deep knowledge in at least one of the following:
Life Sciences Expertise:
Regulatory Compliance:
Experience with
GxP ,
HIPAA , and
21 CFR Part 11
environments.
Data Types:
Familiarity with Clinical Trial data (CDISC standards), RWE (Real World Evidence), and Genomics data.
Use Cases:
Designing architectures for drug discovery R&D or commercial commercial analytics.
Financial Services Expertise:
Regulatory Compliance:
Knowledge of
BCBS 239 ,
GDPR , and
SOX
compliance.
Data Integrity:
Experience building high-concurrency systems for fraud detection, risk modeling, or high-frequency trading.
Security:
Implementing field-level encryption, data masking, and robust IAM policies.
