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dataroles

ETL Developer

Statestreet statestreet.com Open
Hyderabad Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Statestreet. Hyderabad · full-time.

Pay not stated Data Engineering salary

RoleData Engineering
SeniorityMid-level
LocationHyderabad
EmploymentFull-time
PostedNov 2, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and maintain data pipelines across Snowflake, Azure and dbt, bringing data in from multiple upstream systems
  • Create dbt models and advanced SQL transformations for business logic, including reusable and incremental processing
  • Set up Snowflake databases, schemas, tables and views, then tune queries and workloads for efficient processing
  • Add automated checks and reconciliations to validate reporting data, and investigate pipeline or production failures
  • Turn requirements from business and application teams into technical solutions, documenting data flows and supporting releases

What you bring

  • You have hands-on experience developing with Snowflake, including advanced SQL, data loading and performance tuning
  • You have strong dbt development experience with reusable and incremental models, plus macros and Jinja
  • You understand Azure data engineering and have built or supported automated ingestion and orchestration workflows
  • You bring strong SQL skills and experience with high-volume datasets, complex transformations, data modeling and validation

Who this fits

This role suits a mid-level data engineer who can build and troubleshoot Snowflake and dbt pipelines, and support production processing. The role is based in Hyderabad, India.

From the employer


Key Responsibilities

Design, develop and maintain scalable data pipelines using Snowflake, Azure and dbt.

Develop complex data transformation and business logic using dbt models and advanced SQL.

Build and optimize Snowflake objects including databases, schemas, tables, views and other data-processing components.

Develop data ingestion and integration solutions for loading data from multiple upstream systems into the Snowflake platform.

Implement incremental processing, reusable transformation models and dependency-driven workflows using dbt.

Develop automated data-quality checks, reconciliation and validation controls to ensure completeness and accuracy of reporting data.

Optimize SQL queries and Snowflake workloads for performance, scalability and efficient resource utilization.

Work with Azure-based data services and orchestration frameworks supporting ingestion, transformation and downstream delivery.

Troubleshoot data-quality, pipeline and production-processing issues and perform root-cause analysis.

Support development, testing, release and production implementation activities.

Work closely with business analysts, application teams and downstream reporting teams to translate requirements into technical solutions.

Maintain technical documentation covering data flows, transformations, dependencies and operational procedures.

Follow appropriate Git-based version control, code review and CI/CD practices for dbt and data engineering components.

Participate in production support and ensure timely resolution of batch and data-processing failures.

Mandatory Technical Skills

Snowflake

Strong hands-on experience with Snowflake Data Cloud.

Advanced Snowflake SQL and data transformation experience.

Experience working with tables, views, stages, file formats and data-loading patterns.

Good understanding of Snowflake performance optimization and warehouse/resource management.

Experience troubleshooting large-volume data-processing workloads.

Strong hands-on development experience with dbt.

Experience developing reusable dbt models using: Sources Staging and transformation models, Incremental models ,Macros/Jinja

Microsoft Azure

Strong understanding of Azure-based data engineering architecture.

Experience building or supporting automated ingestion and orchestration workflows.

SQL & Data Engineering

Strong SQL development and performance-tuning skills.

Experience handling high-volume datasets and complex transformations.

Strong understanding of:

Data modeling

Data-quality validation


About State Street


Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.


We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.


As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.


Discover more information on jobs at StateStreet.com/careers


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Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.