Software Engineer II, Big Data

tvScientific

Data Engineer at tvScientific designing and implementing data infrastructure in AWS. Collaborating across teams to manage data pipelines and knowledge graphs for a data-heavy organization.

Posted 5/28/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $123,696 - $254,667 per yearWebsite

Tech Stack

Tools & technologies

ApacheAWSCloudScalaSparkSQL

About the role

Key responsibilities & impact

Design and implement robust data infrastructure in AWS, using Spark with Scala
Evolve our core data pipelines to efficiently scale for our massive growth
Store data in optimal engines and formats, matching your designs to our performance needs and cost factors
Collaborate with our cross-functional teams to design data solutions that meet business needs
Design and implement knowledge graphs, exposing their functionality both via Batch Processing and APIs
Leverage and optimize AWS resources while designing for scale
Collaborate closely with our Data Science and Product teams

Requirements

What you’ll need

Production data engineering experience
Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala is preferred
Experience in delivering significant technical initiatives and building reliable, large scale services
Experience in delivering APIs backed by relationship-heavy datasets
Familiarity with data lakes, cloud warehouses, and storage formats
Strong proficiency in AWS services
Expertise in SQL for data manipulation and extraction
Bachelor's degree in Computer Science or a related field
Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
Experience in adtech (nice-to-have)
Experience implementing data governance practices, including data quality, metadata management, and access controls (nice-to-have)
Strong understanding of privacy-by-design principles and handling of sensitive or regulated data (nice-to-have)
Familiarity with data table formats like Apache Iceberg, Delta (nice-to-have)
Previous experience building out a Data Engineering function (nice-to-have)
Proven experience working closely with Data Science teams on machine learning pipelines (nice-to-have)

Benefits

Comp & perks

Health insurance
Stock options
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AWSSparkScalaSQLdata engineeringAPIsdata lakescloud warehousesdata governancemachine learning

Soft Skills

collaborationcritical evaluationintegrityownershipaccountability

Certifications

Bachelor's degree in Computer Science