Top 3 Data modeler datastage Jobs

Senior Data Engineer
Erstom —Minneapolis, MN
- Computer science
- Computer Science
- Customer service
ETL Developer
University of Colorado —Aurora, CO
- $85,000 - $124,729 a year
- Overtime
- Hybrid work
- Background check
- Computer Science
- US work authorization
- Disability insurance
- Health insurance
14d
Programmer Analyst
Kaizen Technologies —United States
- Computer Science
- Bachelor of Science
- Mid-level

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Data Engineer
Sun River Health —Remote
Provider professional license, certification, and DEA fee reimbursement. Organizes and/or leads Informatics projects in the implementation/use of new data…
$100,940.07 - $126,175.08 a year
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ETL Developer
E Logic —Washington, DC
3+ years of cloud ETL engineering experience. Proven experience developing production-grade pipelines using AWS Glue, PySpark, and Databricks.
From $105,000 a year
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Senior Data Engineer

Erstom
Minneapolis, MN

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Job Details

Qualifications

Commercial use (data warehousing systems)
Data Integration (Data management)
Managing projects in an engineering role
Customer service
Presentations for conferences or internal meetings
ETL process automation
Team management
Managing projects
Stakeholder relationship building

Full Job Description

Job Description:

You will be part of a team building the next generation data warehouse platform and will design, develop, and maintain complex extract, transform, and load (ETL) data pipelines using large heterogeneous datasets. You will also build data engineering solutions for complex data models that express business processes. Your expertise with leading technologies and tools such as Oracle, Postgres, Python, etc. will result in a valuable modern data warehouse that supports critical business decisions and data analysis processes. Your collaboration and communication skills will help to establish stakeholder relationships and ensure that your work products are in alignment with project goals. Most importantly, you will be passionate about working with data and will be a significant contributor.

Responsibilities:

Design, develop, and automate scalable data engineering solutions by leveraging cloud infrastructure. Extend or migrate existing data pipelines to new cloud environment.
Lead technical projects involving design and development of data pipelines for complex datasets. Document project plans, outline tasks and milestones, provide estimation of effort.
Work closely with business partners to devise and manage data pipelines, load frequency, data delivery mechanisms, and performance tuning.
Identify and implement best practices for data engineering and software development to ensure quality delivery of enterprise solutions.
Help enable team alignment by participating in code reviews, change management and team meetings.
Develop and maintain detailed technical documentation of data engineering solutions.
Collaborate with key stakeholders, both internal and external, including enterprise data architect, data modelers, and subject matter experts (SMEs).

Qualifications:

Five or more years of professional experience as data engineer. Bachelor’s degree in Computer Science or equivalent experience.
Demonstrated experience in data warehousing and ETL development.
Experience building complex data pipelines using large, disparate data sources.
Demonstrated expert knowledge in SQL.
Demonstrated experience working with relational databases such as Oracle, Postgres and other modern database technologies.
Proficiency in modern programming languages such as Python, R, Java.
Thorough understanding of data movement and transformation tools, such as Informatica, Datastage or equivalent.
Demonstrated experience in selecting tools, methods, techniques, and evaluation criteria for designing optimal data engineering solutions.
Demonstrated experience in leading complex technical projects, including assigning tasks and selecting team members.
Ability to make technical presentations to teams, focus groups, management, and governance committees.
Excellent customer service, communication and collaboration skills.

Preferred Qualifications:

Five years or more experience as data engineer designing and implementing complex data pipelines.
Master’s degree in Computer Science, Information Technology or related field.
Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.).
Experience with AWS technologies.

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