AWS Data Engineer - Data Platform

Zinnia

Dadri

Presencial

INR 1.800.000 - 3.000.000

Jornada completa

Hace 2 días
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Descripción de la vacante

Zinnia is seeking a Data Engineer to build and scale data platforms and pipelines that fuel analytics and machine learning initiatives. You will work within AWS infrastructure, focusing on data governance, reliability, and scalable data feeds across systems.

The role emphasizes SQL and Python development, Snowflake and Airflow expertise, and collaboration with cross-functional teams in a production environment. Based in India, with onsite work expectations.

Formación

  • 4+ years of experience in Data Platform Engineering.
  • Proficient in SQL and Python for data transformation and pipeline development.
  • Experience with Snowflake or similar cloud data warehouses.
  • Experience with Airflow for orchestration and scheduling.
  • Familiarity with dbt for transformations, testing, and documentation.

Responsabilidades

  • Build and maintain scalable data platforms and pipelines powering analytics and data-driven products.
  • Work within AWS infrastructure, implementing and tuning components under senior guidance.
  • Implement telemetry and observability solutions for platform reliability.
  • Provision data infra components (S3, IAM, Lambda, RDS/Aurora) and Snowflake resources using IaC tools.
  • Package, deploy, and manage pipeline components as containerized services (Docker/Kubernetes).
  • Develop and maintain ELT/ETL workflows using Airflow, dbt, and Airbyte.

Conocimientos

SQL proficiency
Python proficiency
Clear written and verbal communication
Agile cross-functional collaboration

Herramientas

Snowflake
Airflow
dbt
Terraform
Kubernetes / EKS

Descripción del empleo

Who We Are

Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.

Who We Are

Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.

Who You Are

You are a Data Engineer who wants to go deep on platform and infrastructure work — building the pipelines, storage, and platform foundations that the rest of the business builds on. You think in terms of well-modeled data, reliable orchestration, and infrastructure that holds up under real production load. You are good with SQL and Python, know your way around AWS core services, and can take a clear set of requirements and turn them into solid, well-tested outcomes. You are curious about how data platforms can be setup, scaled, integrated in the wider application ecosystem and resulting data feeds downstream analytics and machine learning use cases.

What You'll Do
  • Build and maintain scalable, reliable data platforms and pipelines that power analytics and data-driven products across Zinnia.
  • Work within the data platform's AWS infrastructure — storage, IAM, compute and orchestration services — implementing and tuning components under the guidance of senior engineers.
  • Implement and integrate with telemetry and observability solutions for Infrastructure and Platform reliability.
  • Provision and modify data infrastructure components (S3 buckets, IAM roles, Lambda, RDS/Aurora, compute resources) using Terraform, including Snowflake infrastructure-as-code (warehouses, roles, databases), working from existing modules and patterns.
  • Familiarity with streaming or event-driven data (Kafka, Kinesis, or similar)
  • Package, deploy, and manage pipeline components as containerized services (ex: Docker, Kubernetes/EKS, ECS), including EKS cluster upgrades and configuration changes
  • Implement data quality checks, monitoring, and basic lineage so downstream teams can trust the data they're consuming.
  • Contribute to data governance, access control, and cost-optimization practices within AWS and Snowflake.
  • Troubleshoot pipeline and infrastructure issues, escalating and collaborating with senior engineers on complex or systemic problems.
  • Write clear documentation and follow established technical standards for the data platform.
  • Develop and maintain ELT/ETL workflows using Airflow, dbt, and Airbyte (or similar ingestion tools) for self-serve data access
  • Familiarity with AI-assisted engineering tools and platforms (e.g., Claude, Cortex Code), LLM-based workflows, and agentic automation to support infrastructure and platform changes
What You'll Need
  • 4+ years of experience in Data Platform Engineering
  • Hands-on experience with AWS core services (e.g., S3, IAM, compute services)
  • Good hands-on proficiency in SQL and Python for data transformation and pipeline development.
  • Experience with a cloud data warehouse such as Snowflake or similar.
  • Working knowledge of Airflow for orchestration and scheduling, including managed Airflow (MWAA) or similar hosted-Airflow configuration and environment management.
  • Experience/awareness with dbt, including dbt Cloud, for transformations, testing, documentation, and job/environment configuration.
  • Solid understanding of data modeling fundamentals (dimensional and fact-based designs).
  • Comfort working in agile, cross-functional teams alongside more senior engineers, analysts, and data scientists.
  • Clear written and verbal communication skills.
Nice to have:
  • Exposure to MLOps concepts — training data pipelines, feature generation, or model monitoring data.
  • Experience with Airbyte or similar ELT ingestion tools.
  • Familiarity with CI/CD practices for data pipelines, including building and maintaining GitHub repositories and GitHub Actions pipelines.
  • Experience in a regulated industry such as insurance or financial services.
WHAT'S IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done.

Visit our website at www.zinnia.com for more information.

We are an Equal Opportunity employer committed to a diverse workforce.

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

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