Data Engineer

Reach Velocity - Emerging Technology ?? ??; Houston (TX); On-site; USD 110,000 - 150,000; Full time

Job summary

Reach Velocity is seeking a hands-on Data Engineer to build and operate data pipelines powering a centralized platform used by global energy traders, analysts, applications, and AI systems.

You will focus on Python-driven production pipelines, Snowflake data models with dbt, and migrating legacy Oracle components to modern frameworks, while collaborating with analysts and trading users to deliver practical, reliable solutions.

Qualifications

• 3+ years of hands-on Data Engineering experience building and operating production pipelines.
• Strong Python skills, including pandas and modern data-handling practices.
• Strong SQL and data modeling skills.
• Experience with Snowflake or a comparable cloud data warehouse.
• dbt experience is highly preferred.
• Pipeline orchestration experience (Prefect, Airflow, Dagster, etc.).
• Understanding of streaming, caching, time-series, relational, and warehouse environments.
• Strong engineering fundamentals: testing, Git, code reviews, maintainable code.
• Working knowledge of AWS data services and APIs.

Responsibilities

• Build, test, and operate production data pipelines in Python, orchestrated with Prefect.
• Develop and maintain Snowflake data models using dbt.
• Migrate legacy pipelines and Oracle-based components to modern frameworks.
• Work across Kafka, Redis, InfluxDB, Oracle, Snowflake, and AWS.
• Integrate external data from APIs, files, feeds, and web sources.
• Implement data quality, freshness, reconciliation, monitoring, and alerting.
• Contribute to making platform data AI-ready, documented, and discoverable.
• Collaborate with analysts and desk users to translate requirements into practical solutions.
• Ensure production pipelines meet reliability and performance targets.

Skills

Python

SQL

Data modeling

AWS

Git

Testing

Pandas

Energy/Commodities domain

Strong data handling

Tools

Prefect

dbt

Airflow

Kafka

Redis

InfluxDB

Oracle

Docker

Terraform

API development

Job description

We are looking for a hands-on Data Engineer to build and operate the data pipelines and models powering a centralized data platform used by global energy traders, analysts, applications, and AI systems.

Python is the core skill, but the role spans the broader data platform, including Snowflake, Prefect, dbt, Kafka, Redis, InfluxDB, Oracle, and AWS.

You will build production data pipelines, modernize legacy systems, improve data quality and reliability, and work directly with analysts and desk users to ensure the data platform supports real commercial needs.

Key Responsibilities

• Build, test, and operate production data pipelines in Python, orchestrated with Prefect.
• Develop and maintain Snowflake data models using dbt.
• Migrate legacy pipelines and Oracle-based components to modern frameworks and standards.
• Work across Kafka, Redis, InfluxDB, Oracle, Snowflake, and AWS.
• Integrate external data from APIs, files, feeds, and web sources.
• Implement data quality, freshness, reconciliation, monitoring, and alerting.
• Contribute to making platform data AI-ready, documented, and discoverable.
• Work directly with analysts and desk users to understand requirements and deliver practical solutions.

Required Qualifications

• 3+ years of hands-on Data Engineering experience building and operating production pipelines.
• Strong Python skills, including pandas and modern data-handling practices.
• Strong SQL and data modeling skills.
• Experience with Snowflake or a comparable cloud data warehouse.
• Experience with dbt is highly preferred.
• Experience with pipeline orchestration such as Prefect, Airflow, Dagster, or similar.
• Understanding of data technologies across streaming, caching, time-series, relational, and warehouse environments.
• Strong engineering fundamentals including testing, Git/version control, code reviews, and maintainable code.
• Working knowledge of AWS data services.
• Experience with Docker, Terraform, or API development is a plus.

The client is particularly interested in candidates with experience working with data in:

• Oil & Gas
• Energy
• Commodities / Commodity Trading
• Financial Markets / Trading
• Power & Gas Markets

Experience working with market data, fundamental data, trading data, pricing, supply/demand, or energy-market datasets will be strongly preferred.

Ideal Candidate

A production-focused Data Engineer who can build reliable data pipelines, understand the broader platform architecture, and work directly with analysts and trading users.

The ideal profile combines strong Python + SQL + modern data engineering skills with Energy/Commodities domain experience.