Senior Analytics Engineer Data Platform | AWS | Snowflake | dbt

Senior Analytics Engineer Data Platform

Location: Remote / Coimbatore, Tamil Nadu

Engagement: Contractor preferred | Full-time candidates may also be considered

Work Model: Remote-friendly

Coimbatore Requirement: Must be available to travel to our Coimbatore office once per month

About the RoleWe are looking for a highly experienced Senior Analytics Engineer Data Platform who can operate as both a hands-on technical leader and platform owner.

This is not a role for someone who simply executes tickets. We need someone who can own the data platform end-to-end, make strong architectural decisions, build scalable data solutions, establish engineering standards, and confidently communicate technical trade-offs to senior leadership and business stakeholders.

The ideal candidate will be exceptionally strong technically, with deep expertise in AWS, Snowflake, dbt, SQL, Python, data modeling, data governance, and BI, combined with outstanding written and verbal communication skills.

You will work closely with Data, Engineering, Modeling, Actuarial, Compliance, and business teams while owning the roadmap and reliability of the analytics platform.

What You'll Own

Data Platform & Pipeline Engineering

Own the complete data lifecycle ingestion, transformation, modeling, semantic layer, and BI delivery.Build and maintain scalable pipelines across AWS, Snowflake, dbt, Glue, Step Functions, S3, and Lambda.Monitor pipeline health, troubleshoot data issues, and drive resolution with internal teams and external providers.Partner with third-party infrastructure vendors and oversee DataOps practices.Establish engineering standards for reliability, scalability, observability, and maintainability.Data Architecture, Modeling & Governance

Design and evolve enterprise data models across multiple sources, products, and business domains.Build and maintain data dictionaries, business definitions, lineage, and data quality standards.Implement Snowflake security practices including RBAC, dynamic masking, least-privilege access, and performance/cost optimization.Support data governance, auditability, compliance, and security requirements.Systems of Record & AI Data Infrastructure

Design reliable systems of record for core business domains.Implement appropriate versioning, effective dating, and audit history.Support data infrastructure for AI/ML use cases, including feature stores, vector databases, and model input/output pipelines.Semantic Layer & BI

Own and evolve the analytics semantic layer.Build executive-level and operational dashboards.Establish BI development standards and best practices.Translate complex business requirements into scalable analytical solutions.Technical Leadership

Own the technical roadmap for the analytics/data platform.Make architecture and technology decisions with long-term scalability in mind.Mentor junior data and analytics professionals.Communicate technical risks, trade-offs, and recommendations clearly to senior leadership.Work effectively across engineering, business, actuarial, compliance, and external partners.

Must-Have Technical Expertise

We are looking for someone who is genuinely hands-on and technically strong across the data stack.

8+ years of experience in Analytics Engineering, Data Engineering, or a closely related discipline.Expert-level SQL.Strong hands-on Python experience for data engineering, automation, and pipeline development.Deep experience with Snowflake, including:RBACDynamic data maskingPerformance optimizationCost governanceStrong hands-on experience with dbt for transformation, testing, and data modeling at scale.Strong AWS data engineering experience with:AWS GlueStep FunctionsS3LambdaExperience designing enterprise data models and semantic layers.Experience building and owning BI platforms and executive dashboards.Strong understanding of data governance, data quality, lineage, and security.Hands-on experience with Terraform, CloudFormation, or equivalent Infrastructure-as-Code tools.Experience with Git, CI/CD, and modern data engineering practices.Experience with distributed processing such as Spark / AWS Glue / EMR is highly valuable.

Compliance & Data Security

Experience working with regulated or highly sensitive data is strongly preferred.

Knowledge of one or more of the following is highly valuable:

GLBANAIC MDL-668SOC 2 Type IICCPA / CPRAHIPAAData privacy and security controlsAudit trails and evidence collection

Industry ExperienceExperience in Life Insurance, Annuities, Insurance, Actuarial, or broader Financial Services is strongly preferred.

Experience supporting actuarial, modeling, underwriting, or other advanced analytics teams is a significant advantage.

The Person We're Looking For

Technical excellence is non-negotiable.

You should be someone who:

Can independently architect and build complex data platforms.Understands systems deeply rather than simply working within predefined requirements.Can troubleshoot difficult data and .