Data Engineer III - Data Platform
Gurugram, Haryana, India; Hyderabad; Noida, Uttar Pradesh, India; Pune, Maharashtra, India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild and maintain scalable data platforms and pipelines for analytics
Provision and modify AWS and Snowflake infrastructure using Terraform
Develop and maintain ELT/ETL workflows using Airflow, dbt, and Airbyte
Package and manage pipeline components as containerized services
Implement data quality checks, monitoring, and basic lineage
From the employer’s posting
Build and maintain scalable, reliable data platforms and pipelines that power analytics and data-driven products across Zinnia.
Provision and modify data infrastructure components (S3 buckets, IAM roles, Lambda, RDS/Aurora, compute resources) using Terraform
Develop and maintain ELT/ETL workflows using Airflow, dbt, and Airbyte (or similar ingestion tools) for self-serve data access
Package, deploy, and manage pipeline components as containerized services (ex: Docker, Kubernetes/EKS, ECS)
Implement data quality checks, monitoring, and basic lineage so downstream teams can trust the data they're consuming.
What you’ll bring
All qualificationsCore experience
- 4+ years of experience in Data Engineering, with a focus on Data
- Experience with Airbyte or similar ELT ingestion tools.
- Hands-on experience with AWS core services (e.g., S3, IAM, compute services)
- Familiarity with CI/CD practices for data pipelines, including building and maintaining GitHub repositories and GitHub Actions pipelines.
- Strong proficiency in SQL and Python for data transformation and pipeline development.
- Experience in a regulated industry such as insurance or financial services.
Qualification wording
4+ years of experience in Data Engineering, with a focus on Data
Experience with Airbyte or similar ELT ingestion tools.
Hands-on experience with AWS core services (e.g., S3, IAM, compute services)
Familiarity with CI/CD practices for data pipelines, including building and maintaining GitHub repositories and GitHub Actions pipelines.
Strong proficiency in SQL and Python for data transformation and pipeline development.
Experience in a regulated industry such as insurance or financial services.
Tools in this posting
- Python
- SQL
- Airbyte
- AWS
- dbt
- Docker
- Kafka
- Kubernetes
- S3
- Snowflake
- Terraform
- Airflow
Source — Tool mentions in context
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 comfortable 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:
- Hands-on experience with AWS core services (e.g., S3, IAM, compute services) - Strong proficiency in SQL and Python for data transformation and pipeline development. - Experience with a cloud data warehouse such as Snowflake or similar.
- 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
- 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.
- 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.
- 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.
- 4+ years of experience in Data Engineering, with a focus on Data - Hands-on experience with AWS core services (e.g., S3, IAM, compute services) - Strong proficiency in SQL and Python for data transformation and pipeline development.
- 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).
- 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.
- 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 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)
- Strong 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 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.
About Zinnia - Employee Referral
Zinnia is the leading technology platform for accelerating life and annuities growth.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 10, 2026 · 49 days ago
- Recorded sightings
- 22
- Last seen by us
- Oct 21, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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 comfortable 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 Engineering, with a focus on Data
- Hands-on experience with AWS core services (e.g., S3, IAM, compute services)
- Strong 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. Apply by completing the online application on the careers section of our website. 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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- Pay
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- Location & working pattern
Gurugram, Haryana, India; Hyderabad; Noida, Uttar Pradesh, India; Pune, Maharashtra, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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