Data Engineer

Elder Research

Data Engineer for Elder Research designing and maintaining scalable ETL pipelines. Collaborating with teams to implement data standards and ensure data quality.

Posted 7/1/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing, building, and maintaining scalable ETL pipelines while ensuring data quality and governance in alignment with Enterprise Data Management standards. Proficient in SQL and Python for data ingestion and transformation, with hands-on experience in modern data architectures.

Highest-signal resume keywords

ETL Pipeline DevelopmentSQL ProficiencyPython ProgrammingData Quality ManagementDatabricks Unity Catalog

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

ETL PipelineSQLPythonData GovernanceData QualityData ManagementStreaming IngestionBatch IngestionLakehouse ArchitectureData Transformation

Soft Skills

CollaborationProblem-Solving

Tools & Technologies

DatabricksSQL ServerAPIsGraph DatabasesFlat FilesJSONXMLExcel

Industry Keywords

Enterprise Data ManagementFraud DetectionAnomaly DetectionFinancial Oversight

Tech Stack

Tools & technologies

ETLPythonSQLUnity

About the role

Key responsibilities & impact

Join a motivated, career-oriented team as a Data Engineer.
Design, build, and maintain ETL pipelines across diverse data sources.
Implement data management standards and ensure data quality practices.
Collaborate with teams to optimize data loading and management processes.

Requirements

What you’ll need

At least three (3) years of professional experience in data engineering or a related field.
Demonstrated ability to design, build, and maintain scalable ETL pipelines across diverse data sources.
Familiarity with data governance, data quality, and data management practices consistent with Enterprise Data Management (EDM) standards.
Strong SQL and Python skills (or equivalent) to ingest and transform data from flat files, JSON, XML, Excel, APIs, and graph databases.
Hands-on experience loading, managing, and optimizing data within Databricks Unity Catalog and SQL Server managed instances. Proficient with streaming/batch ingestion frameworks and modern Lakehouse architecture.
Proven capability in implementing standard processes to ensure data quality, lineage, reliability, and performance while collaborating with cross-functional teams.
Experience supporting a fraud detection, anomaly detection, or financial oversight analytics environment.

Benefits

Comp & perks

Employee wellness programs
Flexible work arrangements
Professional development opportunities