Senior Data Engineer

Henderson Scott; Dallas (TX); On-site; USD 105,000 - 130,000; Full time

Job summary

Henderson Scott is recruiting experienced Data Engineers to support a cloud data-modernisation programme in the financial-services sector. This opportunity can be at Data Engineer or Senior Data Engineer level, depending on your depth of experience with Snowflake, dbt, Fivetran and AWS.

You will design, develop and optimise scalable data pipelines and reusable data products, with emphasis on data ingestion, transformation, modelling, quality and platform optimisation to deliver trusted data for

Qualifications

• At least five years of professional data-engineering experience.

Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines using Snowflake and dbt.
• Build and manage data-ingestion processes using Fivetran or comparable tools.
• Develop reusable data-transformation frameworks and pipeline patterns.
• Perform source-to-target mapping and support data-migration initiatives.
• Develop and optimise Snowflake databases, schemas and data models.
• Implement data-quality, validation, reconciliation and monitoring controls.
• Optimise SQL queries, warehouse utilisation and overall platform performance.
• Collaborate with architects, business stakeholders and analytics teams to deliver trusted data products.
• Support DataOps, Git and CI/CD practices across the data-engineering environment.
• Ensure solutions follow security, governance and data-management standards.
• Prepare high-quality datasets for analytics, AI and GenAI use cases.

Skills

SQL

Python

Data pipelines

Data warehousing

Source-to-target mapping

Data quality

CI/CD

Git

DataOps

Tools

Snowflake

dbt

Fivetran

AWS

Git

Terraform

Snowpipe/Tasks

Snowflake CoCo

Job description

Salary: $105,000–$130,000 per annum + bonus and benefits

Employment: Full-time W2

Work authorization: U.S Citizens, Green Card or Green Card EAD

Please note: Candidates must be able to attend an onsite client interview in Dallas. No exceptions can be made.

We are recruiting experienced Data Engineers to support a major cloud data-modernisation programme within the financial-services sector. This opportunity can be considered at either Data Engineer or Senior Data Engineer level, depending on the successful candidate’s experience and technical depth.

You will design, develop and optimise scalable data pipelines and reusable data products using Snowflake, dbt, Fivetran and AWS technologies. The role will involve working across data ingestion, transformation, modelling, quality and platform optimisation, helping deliver trusted data for analytics and AI-driven initiatives.

Key responsibilities:

• Design, develop and maintain scalable ETL/ELT pipelines using Snowflake and dbt.
• Build and manage data-ingestion processes using Fivetran or comparable tools.
• Develop reusable data-transformation frameworks and pipeline patterns.
• Perform source-to-target mapping and support data-migration initiatives.
• Develop and optimise Snowflake databases, schemas and data models.
• Implement data-quality, validation, reconciliation and monitoring controls.
• Optimise SQL queries, warehouse utilisation and overall platform performance.
• Collaborate with architects, business stakeholders and analytics teams to deliver trusted data products.
• Support DataOps, Git and CI/CD practices across the data-engineering environment.
• Ensure solutions follow security, governance and data-management standards.
• Prepare high-quality datasets for analytics, AI and GenAI use cases.

Required experience:

• At least five years of professional data-engineering experience.
• Three or more years of recent, hands‑on experience with Snowflake and dbt.
• Strong experience building production ETL/ELT pipelines.
• Advanced SQL and solid Python capability.
• Experience with Fivetran or a similar cloud-based ingestion platform.
• Strong understanding of data warehousing, data modelling and source-to-target mapping.
• Experience implementing data-quality and reconciliation processes.
• Knowledge of Git, CI/CD and modern DataOps practices.
• Ability to work onsite in Dallas four days per week.

For consideration at Senior Data Engineer level, candidates should also demonstrate:

• Approximately seven or more years of data-engineering and integration experience.
• Hands‑on AWS Glue and PySpark experience.
• Experience designing AWS and Snowflake data‑lake solutions.
• Ownership of enterprise‑scale ingestion and transformation frameworks.
• Experience creating reusable automation and pipeline frameworks.
• Strong understanding of cloud‑native architecture and infrastructure automation.
• Snowpipe, Streams and Tasks.
• Snowflake data sharing and role‑based security.
• Query optimisation and warehouse management.
• AWS S3 and Lambda.
• Terraform or other infrastructure‑as‑code tools.
• Snowflake CoCo or comparable AI‑assisted data‑engineering tools.
• Experience working within banking or another highly regulated environment.

This is an excellent opportunity to join a significant enterprise data‑transformation programme and work with a modern Snowflake, dbt, Fivetran and AWS technology stack.