Data Engineer

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About SII Group USA

SII Group USA is part of the global SII Group, a leading provider of engineering, consulting, and digital transformation services. Our teams partner with global enterprises to design, build, and scale high-performance technology solutions. We are expanding our data engineering capabilities in India and seeking passionate technologists committed to excellence, innovation, and delivery velocity.

Role Overview

Data Engineering Specialist

Key Responsibilities

1. Data Engineering & Lakehouse Development

• Design, build, and maintain scalable data pipelines using

  PySpark

  and

  Databricks

  .
• Implement and optimize

  Delta Lake / Lakehouse

  architectures for high-volume and real-time workloads.
• Ensure robust data ingestion, transformation, and export workflows with scalable orchestration.

2. Cloud Integration (GCP & AWS)

• Develop integrations between

  GCP services

  , Databricks, and enterprise systems.
• Utilize AWS services for complementary workloads (S3, Lambda, EC2, IAM, API Gateway, etc.).
• Manage hybrid cloud data flows and cross-platform integrations securely and efficiently.

3. API / REST-Based Data Export

• Build and manage

  API/REST-based data export triggers

  and automated delivery pipelines.
• Architect and optimize data exposure layers for downstream consumption and client interfaces.

4. Infrastructure as Code & DevOps

• Implement

  IaC

  using

  Terraform

  for cloud resource provisioning and environment management.
• Develop and maintain

  CI/CD pipelines

  for code deployments, Databricks jobs, and infrastructure automation.
• Ensure repeatable, scalable, and compliant deployment workflows.

5. Data Modeling & SQL Optimization

• Design logical and physical

  data models

  , export structures, and schema standards.
• Write and tune complex

  SQL

  queries with a focus on performance at scale.
• Implement best practices for partitioning, caching, indexing, and cost optimization.

6. Security, Governance & IAM

• Apply

  data governance

  best practices across metadata, lineage, quality, and access control.
• Configure and manage

  IAM

  , cluster security, encryption, credential handling, and audit logging.
• Ensure compliance with enterprise security policies and client requirements.

7. Performance, Scalability & Reliability

• Optimize ETL/ELT workflows for cost, latency, and throughput.
• Implement monitoring, alerting, and auto-scaling strategies across cloud platforms.
• Collaborate with architecture teams to enable long-term scalability and resilience.

8. Client Delivery & Ramp-Up Support

• Support rapid client onboarding and

  delivery velocity enhancement

  .
• Collaborate closely with product owners, project managers, and client stakeholders.
• Provide guidance to junior engineers, perform code reviews, and help build best-practice frameworks.

Required Skills & Experience

• 4–10 years of experience in

  data engineering

  (range can be adjusted).
• Strong hands-on experience with

  PySpark

  and

  Databricks

  .
• Proven expertise in

  Delta Lake / Lakehouse

  implementations.
• Experience with both

  GCP

  (BigQuery, GCS, Pub/Sub, IAM, etc.) and

  AWS

  (S3, Lambda, Glue, Redshift, etc.).
• Proficiency in

  Terraform

  ,

  CI/CD tools

  (Azure DevOps, GitHub Actions, GitLab CI, Jenkins, etc.).
• Strong SQL skills, including performance tuning and query optimization.
• Experience with API integrations, REST services, and automated triggers.
• Understanding of data security, governance frameworks, and IAM policies.
• Experience working in agile delivery teams, with client-facing exposure preferred.

Preferred Qualifications

• Databricks certifications (Data Engineer Associate/Professional).
• GCP or AWS cloud certifications.
• Experience supporting enterprise-scale data programs.
• Knowledge of data quality frameworks (e.g., Deequ, Great Expectations).

What We Offer

• Opportunity to work with global clients and cutting-edge data technologies.
• Collaborative culture with strong focus on innovation.
• Competitive compensation, continuous learning opportunities, and global career mobility