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Data Engineer
- Dallas, Texas, United States
- Dallas, Texas, United States
Über
at least 3 years of hands‑on data engineering expertise , you will step in as the critical link bridging the gap between raw infrastructure and enterprise‑wide intelligence. You will collaborate closely with data architects, analysts, and business leaders to design and maintain robust integration pipelines that deliver absolute truth in data. If you are passionate about refining data quality and building seamless delivery systems that support a truly data‑driven culture, we want you on our team.
Why should you apply here?
With a proud 40-year legacy, this firm stands at the forefront of its industry, setting the standard for excellence and innovation.
Home to over 800 dedicated professionals, the company thrives with the energy and agility of a mid‑size powerhouse.
As a privately held company with an Employee Stock Ownership Program, every employee is empowered to shape the company’s future.
The arrival of a visionary CIO in 2023 sparked rapid IT expansion, quadrupling the team from 5 to 20 members in record time.
Cutting‑edge automation and robust security are at the heart of every initiative.
Nearly all projects are new development, backed by the latest resources and tools to ensure success.
IT champions open communication, seamless collaboration, and a culture where everyone thrives.
Enjoy continuous opportunities to learn, grow, and advance their careers.
What will you be doing?
Design, build, and manage data pipelines that power real‑time insights and drive impactful decisions both in batch and streaming environments.
Bring data to life by developing and maintaining dynamic ETL/ELT processes using cutting‑edge tools like Azure Data Factory and Databricks.
Partner closely with stakeholders to uncover needs and deliver data that fuels insightful reporting and analytics.
Collaborate with architects and analysts to shape, cleanse, and enrich data, ensuring it’s ready to unlock hidden opportunities.
Take ownership of data solution performance by monitoring, optimizing, and ensuring every solution meets and exceeds expectations.
Get involved in data governance and metadata management to help set the standards that keep data assets trustworthy and valuable.
Champion data quality by implementing robust validation, profiling, and quality checks across every pipeline.
Tackle data challenges head‑on and provide swift support to production systems when issues arise.
Contribute to building enterprise data models and master data management solutions that set the foundation for trusted information.
Safeguard data by upholding the highest standards for security, privacy, and compliance.
Stay ahead of the curve by exploring new trends and technologies in the ever‑evolving world of data engineering.
What are the minimum qualifications?
Bachelor’s degree in Computer Science, Information Systems, or related field; Master’s preferred.
3+ years of hands‑on experience architecture‑building within the Microsoft Azure stack, specifically utilizing
Azure Data Factory (ADF)
for orchestration and
Azure Databricks
or
Synapse Analytics
for heavy data processing.
Proven experience designing and building robust ETL/ELT pipelines
Proven experience designing and optimizing cloud data warehouses or lakehouses (e.g., Azure Data Lake Storage Gen2, Snowflake on Azure) to ensure high‑performance reporting and analytics.
Strong
SQL
skills for complex data transformations, performance tuning, and optimizing query runtimes to ensure efficient data delivery.
Proficiency in
Python
or with a preference for experience using
dbt (Data Build Tool)
to automate transformations, reduce manual data prep, and streamline the semantic layer.
Experience building automated data validation, profiling, and monitoring frameworks (e.g., Great Expectations, dbt tests, or custom Azure alerts) to guarantee the delivery of "trusted data."
Experience with Azure Data Factory, Databricks, Synapse, or equivalent cloud‑based data tools.
Proficiency in SQL optimization, Python, and working with large‑scale data sets.
Strong understanding of data modeling, warehousing, and governance principles.
Proficient with
Git
and modern CI/CD deployment pipelines to ensure stable, version‑controlled code releases.
Experience building and maintaining data pipelines in an enterprise level environment, including a cloud or hybrid environment.
Strong collaboration skills and ability to work cross‑functionally.
Excellent attention to detail and problem‑solving skills.
Ability to manage multiple priorities and meet deadlines.
Salary: 115k – 130k, Excellent medical insurance, Employee Stock Ownership Plan, 401(k)
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Sprachkenntnisse
- English
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