Lead Data Engineer

Jobot; Salt Lake City (UT); Remote; USD 150,000 - 190,000; Full time

Job summary

An innovative firm is seeking a Lead Data Engineer to spearhead the development of cutting-edge data solutions in the financial services sector. This full-time, remote role offers a competitive salary and the chance to work in a dynamic environment focused on solving complex data challenges. You will lead the design of data pipelines, collaborate with cross-functional teams, and drive best practices in data engineering. Join a team where your expertise will directly impact the financial landscape and help shape the future of data-driven decision-making.

Qualifications

• 5+ years of experience in data engineering with a focus on data pipelines.
• Proven ability to design and implement data architectures.

Responsibilities

• Lead the design and implementation of end-to-end data pipelines.
• Collaborate with teams to develop innovative data solutions.

Skills

Data Engineering

Python

TSQL

SQL Databases

Data Pipelines

Data Modeling

Cloud Platforms

Problem Solving

Tools

Apache Airflow

Docker

Azure

Snowflake

DBT

SSIS

Job description

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This range is provided by Jobot. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$150,000.00/yr - $190,000.00/yr

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Remote - Lead Data Engineer - up to $190K base

Join a team building systems to make data-driven business decisions.

This Jobot Job is hosted by Chuck Wirtz.

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About the Role

Our client, in the financial services industry, is seeking a Lead Data Engineer to join their team. This is a full-time, direct hire, remote role offering a base salary of $150-190K plus benefits, depending on experience.

Why Join Us?

This role is ideal for someone who thrives in a dynamic, fast-paced environment, enjoys solving complex data problems, and is passionate about driving innovation in data engineering. Make an impact on the financial landscape with cutting-edge data solutions!

Core Responsibilities

• Lead the design and implementation of end-to-end data pipelines, from extraction (API, scraping, pyodbc) to cleansing/transformation (Python, TSQL) and loading into SQL databases or data lakes.
• Oversee the development of robust data architectures supporting efficient querying and analytics.
• Collaborate with data scientists, developers, BI teams, and stakeholders to develop data solutions.
• Ensure smooth coordination between engineering and other teams to translate business requirements into technical solutions.
• Guide development of data models and schemas optimized for relational and dimensional architectures.
• Lead creation of scalable, reliable data models, optimizing for performance and usability.
• Develop and maintain infrastructure leveraging cloud platforms like Azure and containerization technologies like Docker.
• Utilize modern data platforms such as Snowflake and Fabric effectively.
• Manage data pipelines using tools like Apache Airflow, Prefect, DBT, and SSIS for scalable, reliable ETL processes.
• Implement testing, monitoring, and validation for all data systems and pipelines.
• Drive continuous improvement in data engineering practices.
• Promote best practices, clean code, and rigorous testing within the team.

Experience & Qualifications

• 5+ years in data engineering roles, with proven experience in developing and maintaining data pipelines and architectures.
• Experience with large-scale data platforms and cloud environments.
• Strong background in relational databases, data modeling, and cloud-native solutions.
• Familiarity with tools like Apache Airflow, Prefect, and cloud storage platforms.
• Excellent problem-solving skills for navigating complex technical challenges.

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Jobot is an Equal Opportunity Employer. We celebrate diversity and consider all qualified candidates without discrimination based on race, color, religion, age, sex, national origin, disability, veteran status, sexual orientation, gender identity, or expression.