Senior Data Engineer

Bitful

. Build and maintain data pipelines and datasets supporting reporting, visualization, machine learning and data-driven decision making across finance, sales, supply chain, marketing and other business functions .

Posted 10/13/2026contractRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining scalable data pipelines and datasets, with strong proficiency in Python, PySpark, and SQL. Capable of integrating data from multiple sources and providing technical guidance while collaborating with cross-functional teams.

Highest-signal resume keywords

Data EngineeringSQL ProficiencyPython ProgrammingDatabricks ExperienceETL/ELT Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData ModelingDatabase DesignData WarehousingData ValidationData TransformationAutomated TestingCI/CD PracticesData Quality ImprovementPerformance Optimization

Soft Skills

Strong CommunicationCollaboration

Tools & Technologies

DatabricksApache SparkTableauSpotfireOracleInformatica

Certifications & Qualifications

Databricks Certification

Industry Keywords

Cloud Data PlatformsBusiness IntelligenceData VisualizationData-Driven Decision MakingSource Control

Tech Stack

Tools & technologies

ApacheCloudETLInformaticaOraclePySparkPythonSparkSQLTableau

About the role

Key responsibilities & impact

Build and maintain data pipelines and datasets supporting reporting, visualization, machine learning and data-driven decision making across finance, sales, supply chain, marketing and other business functions
Develop and maintain scalable data pipelines and reusable datasets within a Databricks lakehouse environment
Ingest, validate, clean and transform structured and unstructured data from multiple sources using Python, PySpark and SQL
Build data models and reporting datasets supporting Tableau and established analytics tools such as Spotfire
Integrate established data warehouse and reporting systems with modern cloud analytics platforms
Improve pipeline reliability, data quality and processing performance
Implement automated testing, monitoring, documentation and CI/CD practices
Partner with analysts, architects, developers and business stakeholders to deliver practical data solutions
Provide technical guidance, review code and mentor other data engineers

Requirements

What you’ll need

7+ years of experience in data engineering, including building and supporting production data pipelines
Strong SQL skills and a solid understanding of data modeling, database design and data warehousing
Hands-on experience with Databricks, Apache Spark and cloud data platforms
Strong proficiency in Python and PySpark
Experience developing ETL/ELT pipelines and integrating data from multiple source systems
Experience preparing reliable datasets for Tableau or comparable business intelligence tools
Familiarity with source control, automated testing and CI/CD practices
Ability to troubleshoot complex data issues and optimize pipeline performance
Strong communication skills and experience collaborating with technical teams and business stakeholders
Experience with Spotfire, Oracle, Informatica, R or data virtualization preferred
Databricks certification preferred