Data Engineer

Abacus Group

. Develop and maintain ETL pipelines using Python and SQL Server for data ingestion, transformation, and integration from structured files and RESTful APIs .

Posted 9/28/2026full-timeRemote • United StatesJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in developing and maintaining ETL pipelines using Python and SQL Server, with a strong focus on data quality, security, and compliance in regulated environments. Demonstrates expertise in SQL, data integration from RESTful APIs, and collaboration with cross-functional teams.

Highest-signal resume keywords

Python ProgrammingSQL Server Database ManagementETL Pipeline DevelopmentAzure Data FactoryData Quality Assurance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLT-SQLETL ConceptsData ValidationData ModelingRESTful APIsAzure SQLAzure Blob StoragePower BI

Soft Skills

Analytical SkillsProblem-Solving SkillsCollaborationAdaptabilityCommunication

Tools & Technologies

Azure Data FactoryAzure SQLAzure Blob StorageGitPower BI

Industry Keywords

Data EngineeringHealthcare ComplianceFinancial Services ComplianceHIPAASOC2

Tech Stack

Tools & technologies

AzureETLPythonSQL.NET

About the role

Key responsibilities & impact

Develop and maintain ETL pipelines using Python and SQL Server for data ingestion, transformation, and integration from structured files and RESTful APIs
Write, test, and debug Python code for data processing, automation, and basic integrations
Create and maintain T-SQL queries, views, and stored procedures for business logic and reporting
Assist in building and operating workflows using Azure Data Factory, Azure SQL, and Azure Blob Storage
Monitor data pipelines and troubleshoot data quality issues, pipeline failures, and performance problems
Follow data quality, security, and compliance procedures in regulated environments such as healthcare and financial services
Collaborate with data analysts, software engineers, and DevOps teams
Participate in code reviews and implement feedback
Create and maintain documentation for data pipelines, logic, and operational processes

Requirements

What you’ll need

1–4 years of professional experience in Data Engineering, Software Engineering, or a related technical role — Required
Strong hands-on proficiency in Python, including writing functions, handling errors, and debugging code — Required
Experience working with relational databases, preferably SQL Server — Required
Strong working knowledge of SQL, including joins, aggregations, subqueries, and basic performance considerations — Required
Exposure to integrating or consuming data from RESTful APIs or external data sources — Required
Familiarity with Git or similar version control systems — Required
Strong analytical and problem-solving skills with the ability to learn quickly — Required
Exposure to Azure data services such as Azure Data Factory, Azure SQL, or Blob Storage
Basic understanding of ETL concepts, data validation, and pipeline monitoring
Familiarity with data modeling fundamentals, including tables, keys, and relationships
Awareness of data security, privacy, and compliance standards such as HIPAA and SOC2
Experience with Power BI or other data visualization tools
Basic understanding of application systems or APIs built using .NET or similar frameworks
Ability to design and support scalable ETL pipelines using Python and SQL Server
Ability to develop and optimize T-SQL stored procedures
Ability to support secure and efficient data workflows using Azure Data Factory, Azure SQL, and Azure Functions
Ability to help ensure data quality, lineage, and compliance requirements are maintained
Ability to collaborate with software engineering, data analytics, security, and DevOps teams
Ability to monitor and troubleshoot pipeline failures and data discrepancies
Ability to participate in code reviews and continuously improve engineering practices
Bachelor’s Degree — Preferred