Data Engineer

Description

Position Description

We are seeking a Data Engineer with proven hands-on experience with the design and development of highly available data management platforms and solutions for both on-prem and Azure-based cloud environments. This hands-on, technical role will partner closely with data scientists, analysts, and business stakeholders to ensure that data is accurate, accessible, and optimized for analytics, reporting, and operational needs. This resource will play a key role in building scalable data pipelines and integrations while championing best practices, and leading strategic data initiatives across teams.

Key Responsibilities

Develop and implement secure, scalable data pipelines using Azure Data Factory, Azure Functions, and Azure Data Lake Storage

Design and build reliable ETL/ELT processes using Python (pandas, PySpark), SQL, and SSIS, integrating data from diverse sources including REST APIs and various file formats (CSV, JSON, XML, Parquet)

Collaborate cross-functionally to gather requirements and translate business needs into technical deliverables

Detect and resolve data quality issues; implement automated audits and monitoring processes

Participate in schema design and performance tuning

Mentor and support junior engineers across data engineering, analytics, and BI teams

Participate in code reviews, promoting clean, well-documented, and testable code

Stay current on trends in data engineering and cloud technologies, identifying opportunities to innovate

Minimum Requirements

5 years of experience in data engineering, including

1+ years with Azure cloud-native solutions

3+ years with SQL Server Integration Services (SSIS)

Critical Skills

Expertise in MS SQL Server, SSIS, Python (pandas, PySpark), Azure Data Factory, Azure Functions and Azure Data Lake Storage.

Experience working with a variety of file formats (e.g., CSV, JSON, XML, Parquet).

Familiarity using REST APIs for data extraction and integration.

Proven experience designing and implementing data solutions.

Good understanding of cloud architecture, data warehousing and modern data stack components.

Additional Skills & Qualifications

Demonstrated ability to perform root cause analysis on data and processing issues

Strong problem-solving skills with the ability to explain technical concepts to non-technical audiences

A successful history of manipulating, processing and extracting value from large disparate datasets

Experience with Big Data technologies such as Databricks, Spark, or Azure Synapse

Knowledge of CI/CD workflows, version control, and agile development practices

Familiarity with data governance, privacy, and compliance frameworks

Experience with data warehousing, analytics tools, and BI platforms

Education

4-year degree in computer science, engineering or other related IT field of study, or equivalent professional work experience

Physical Requirements

General office demands

Prolonged periods of sitting at a desk and working on a computer.

Frequent reaching, handling, and fine manipulation for using office equipment, filing, and managing paperwork.

Manual dexterity sufficient to operate a keyboard, mouse, and other office tools.

Occasional standing, walking, and bending.

Ability to lift up to 10-20 pounds occasionally.

Vision abilities required include close vision for computer work and reading documents.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Required

Preferred

Job Industries

Other

Full Time