Lead Data Engineer / Data Eng Architect (AWS)

About Naveera:

Naveera Technology LLC is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development, and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting, we help organizations transform raw data into actionable business value.

With a team of 100+ employees and successful delivery of 5+ global projects, Naveera serves clients across multiple industries and geographies through agile delivery models and proven engineering practices.

We're Hiring: Lead Data Engineer/ Data Architect (AWS & GCP) 

Skills Required: AWS S3, Glue, Redshift, Python, PySpark, Data Build Tool (DBT), Medallion & Serverless Architecture, Complex SQL Queries

Job Location: Madurai

Mode: Remote (Quarterly travel to the Madurai office is required, with a mandatory 5-working-day stay. Please note that accommodation and travel expenses will not be reimbursed by the company.)

Job Type: Full-Time

Experience: 10 to 15 Years

Shift Timing: 2 PM to 11:30 PM IST (Extended work may be required based on business needs)

Interview Process:

L1 Technical Discussion: Virtual Discussion Via Gmeet.

L2 Technical Discussion: Virtual Discussion Via Gmeet.

CTO Technical Discussion: Virtual Discussion Via Gmeet.

Client Interview: Virtual

HR Discussion: Virtual

Onboarding: Virtual Onboarding

Job Title: Lead Data Engineer/ Data Architect (AWS & GCP) 

Strategic and hands-on Architect with over 10+ years of experience in data engineering and cloud architecture. Expert in designing high-performance AWS Data Lakehouses utilizing the Medallion Architecture (Bronze/Silver/Gold) to drive business intelligence at scale. Proven track record of leading complex data migrations (Snowflake/Redshift consolidations) and implementing robust Data Governance frameworks. Specialized in optimizing AWS spend through advanced DPU tuning, Redshift Serverless management, and hybrid dbt Core/Cloud configurations.

Core Competencies

●Architectural Leadership: Medallion Lakehouse Design, Multi-tenant Data Modeling, Schema-on-read/write.

●AWS Ecosystem: Glue (ETL/DataBrew/DQ), Redshift (Provisioned & Serverless), S3, Athena, Step Functions.

●Data Ops & Governance: Terraform (IaC), CI/CD, OpenLineage, Data Quality Frameworks, Lake Formation.

●Transform & Model: Advanced dbt (Data Build Tool) modeling, PySpark, SQL Optimization, CDC (AWS DMS).

●Strategic Impact: Technical Roadmap development, Cost Optimization (FinOps), Mentoring Mid-Level Engineers.

Key Responsibilities

●Architectural Strategy: Define and implement end-to-end Data Lakehouse solutions on AWS, ensuring seamless transitions across Bronze, Silver, and Gold/Atomic layers for enterprise-wide consumption.

●Infrastructure & Automation: Lead the automation of cloud infrastructure using Terraform, ensuring secure, repeatable deployments with integrated S3 encryption and IAM least-privilege protocols.

●Performance & Cost Engineering: Orchestrate large-scale performance tuning initiatives, including Parquet partitioning strategies, DPU optimization in Glue, and Redshift distribution/sort key refinements to reduce latency and cloud spend.

●Data Governance & Quality: Establish automated Data Quality gates using AWS Glue Data Quality and dbt tests; chair Governance Steering committees to ensure data lineage and metadata integrity.

●ETL/ELT Orchestration: Design complex, event-driven workflows using Step Functions and Airflow, integrating AWS DMS for real-time CDC from legacy SQL Server/OLTP systems.

●Cross-Functional Leadership: Serve as the primary technical liaison between Data Science, BI teams (Power BI/Fabric), and Business Stakeholders to translate clinical and operational metrics into scalable data models.

Technical Skills & Qualifications

●Years of Experience: 10+ years in Data Engineering/Architecture, with 5+ years of dedicated AWS specialization.

●Advanced Programming: Expert-level Python, PySpark, and complex SQL window functions.

●Warehousing & Lakes: Deep expertise in Amazon Redshift (including Serverless scaling/warm-up optimization) and Snowflake.

●Frameworks: Mastery of dbt for modular modeling and AWS Glue for serverless integration.

●DevOps: Advanced proficiency in Terraform, GitHub Actions, and containerized data workloads.

●Industry Knowledge: Experience defining clinical/business KPIs (e.g., conversion tracking, referral metrics) and managing multi-location data structures. Experience in HIPAA standards will be a plus

Preferred Qualifications

●Certifications: AWS Certified Solutions Architect Professional or AWS Certified Data Engineer Associate.

●Education: Bachelors or Masters degree in Computer Science, Information Systems, or a related technical field.

●Expertise: Familiarity with Microsoft Fabric (F-Capacities) and Power BI Embedded integration within AWS-hosted applications.