Emergent Software
Senior Data Engineer - Contract
Emergent Software - Minneapolis, Minnesota, United States, 55400
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Overview
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Overview
** This is a 6-12+ month contract opportunity with our client located in Minneapolis, MN. On-site requirement is 4 days per week. Candidates must be authorized to work in the United States without the need for sponsorship. **
We are seeking a
Senior Data Engineer
to join a fast-paced, growing data engineering team within a forward-thinking investment firm. This role is ideal for a technically skilled data professional with strong experience in
SQL
and
Python , and a passion for building data pipelines, modeling, and delivering modern data solutions. You must be comfortable working with
both structured and unstructured data,
and have a strong interest in cloud technologies. While experience with
AWS ,
DBT , and
Snowflake
is a plus, the team is open to training the right candidate in these tools. Primary Duties Build and maintain scalable data pipelines using
SQL
and
Python . Work with both structured and unstructured data to support analytical and operational use cases. Support cloud data engineering projects, especially those leveraging AWS (training available). Collaborate on data modeling and transformation efforts across teams. Assist with documentation, QA, and code reviews to ensure data quality and system reliability. Communicate effectively with engineers, analysts, and business partners to deliver timely data solutions. Continuously identify opportunities to optimize and improve data workflows. Required Qualifications Strong experience with SQL and Python. Ability to work confidently with structured and unstructured data. Strong analytical thinking and problem-solving skills. Excellent written and verbal communication skills. Self-starter who is eager to learn and grow in a fast-moving environment. Nice to Have Skills Experience with
DBT
(Data Build Tool). Familiarity with
Snowflake
or similar cloud data platforms. Exposure to
AWS
services (e.g., S3, Redshift, Glue, Lambda). Experience with data visualization tools such as Looker (training provided). Knowledge of version control (Git), CI/CD, and workflow orchestration tools like Airflow. Background in financial services or data-intensive business environments.
#EmergentStaffing
We are seeking a
Senior Data Engineer
to join a fast-paced, growing data engineering team within a forward-thinking investment firm. This role is ideal for a technically skilled data professional with strong experience in
SQL
and
Python , and a passion for building data pipelines, modeling, and delivering modern data solutions. You must be comfortable working with
both structured and unstructured data,
and have a strong interest in cloud technologies. While experience with
AWS ,
DBT , and
Snowflake
is a plus, the team is open to training the right candidate in these tools. Primary Duties Build and maintain scalable data pipelines using
SQL
and
Python . Work with both structured and unstructured data to support analytical and operational use cases. Support cloud data engineering projects, especially those leveraging AWS (training available). Collaborate on data modeling and transformation efforts across teams. Assist with documentation, QA, and code reviews to ensure data quality and system reliability. Communicate effectively with engineers, analysts, and business partners to deliver timely data solutions. Continuously identify opportunities to optimize and improve data workflows. Required Qualifications Strong experience with SQL and Python. Ability to work confidently with structured and unstructured data. Strong analytical thinking and problem-solving skills. Excellent written and verbal communication skills. Self-starter who is eager to learn and grow in a fast-moving environment. Nice to Have Skills Experience with
DBT
(Data Build Tool). Familiarity with
Snowflake
or similar cloud data platforms. Exposure to
AWS
services (e.g., S3, Redshift, Glue, Lambda). Experience with data visualization tools such as Looker (training provided). Knowledge of version control (Git), CI/CD, and workflow orchestration tools like Airflow. Background in financial services or data-intensive business environments.
#EmergentStaffing