This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Senior Data Engineer at tvScientific, you will be a key player in implementing the robust data infrastructure to power our data-heavy company. This is an individual contributor role, where you will work to define and implement a strategic vision for data engineering within the organization. - 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 - Collaborate with our cross-functional teams to design data solutions that meet business needs - Built out fault-tolerant batch and streaming pipelines - Leverage and optimize AWS resources while designing for scale - Collaborate closely with our Data Science and Product teams Qualifications - Production data engineering experience - Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala - Familiarity with data lakes, cloud warehouses, and storage formats - Strong proficiency in AWS services - Expertise in SQL for data manipulation and extraction - Excellent written and verbal communication skills - Bachelor's degree in Computer Science or a related field Requirements - Experience in adtech - Experience implementing data governance practices, including data quality, metadata management, and access controls - Strong understanding of privacy-by-design principles and handling of sensitive or regulated data - Familiarity with data table formats like Apache Iceberg, Delta Benefits Information regarding the culture at Pinterest and benefits available for this position can be found here . Company Description tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Staff Data Engineer at tvScientific, you will be a key player in implementing the robust data infrastructure to power our data-heavy company. This is an individual contributor role, where you will work to define and implement a strategic vision for data engineering within the organization. - 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 Qualifications - Production data engineering experience - Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala - 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 - Excellent written and verbal communication skills - Bachelor's degree in Computer Science or a related field Requirements - Experience in adtech - Experience implementing data governance practices, including data quality, metadata management, and access controls - Strong understanding of privacy-by-design principles and handling of sensitive or regulated data - Familiarity with data table formats like Apache Iceberg, Delta - Previous experience building out a Data Engineering function - Proven experience working closely with Data Science teams on machine learning pipelines In-Office Requirement Statement We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. Relocation Statement This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. Salary Information At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. US based applicants only $155,584 — $320,320 USD

HMA is the premier third-party health plan administrator across the PNW and beyond. We relentlessly deliver on our promise to provide medium to large-size employers with customized health plans. We offer various high-quality, affordable healthcare plan options supported with best-in-class customer service.  We are proud to say that for three years, HMA has been chosen as a ‘Washington’s Best Workplaces’ by our Staff and PSBJ™. Our vision, ‘Proving What’s Possible in Healthcare™,’ and our values, People First!, Be Extraordinary, Work Courageously, Own It, and Win Together, shape our culture, influence our decisions, and drive our results. What we are looking for: We are always searching for unique people to add to our team. We only hire people that care deeply about others, thrive in evolving environments, gain satisfaction from being part of a team, are motivated by tackling complex challenges, are courageous enough to share ideas, action-oriented, resilient, and results-driven.  What you can expect: You can expect an inclusive, flexible, and fun culture, comprehensive salary, pay transparency, benefits, and time off package with plenty of personal development and growth opportunities. If you are looking for meaningful work, a clear purpose, high standards, work/life balance, and the ability to contribute to something important, find out more about us at: https://www.accesshma.com/ How YOU will make a Difference: The Data Integrations Engineer plays a key role ensuring the smooth transmission and processing of data between internal and external systems. The ideal candidate will have experience in writing complex SQL queries, creating ETL’s, and understanding inbound and outbound EDI transactions and protocols. The incumbent will work closely with IT, business partners, and external vendors to implement new systems and update existing systems. Excellent communication skills are a must to ensure the continued smooth operation of the company. What YOU will do: - Design, code, test, deploy, maintain, monitor and execute production ETL processes - Investigate production ETL issues / problems - Work with business users to gather requirements and design, create, and implement database systems & applications. - Lead troubleshooting episodes and communicate solutions/resolutions to the team - Translate concepts to requirements and technical design - Complete projects and development activities timely and accurately while following the System Development Life Cycle (SDLC) - Develop, implement, and optimize stored procedures and functions using T-SQL - Analyze existing SQL queries for performance improvements. - Create and update EDI document mappings - Take ownership of SQL development for future products and enhancements of existing products. - Must possess analytical and complex problem-solving skills.

• Close collaboration with data scientists, ML engineers, and product teams to translate requirements into scalable, maintainable data solutions • Build, document, and maintain robust data pipelines using tools like dbt, Dagster, Snowflake, Estuary, and Airbyte. • Develop deployment and release of functionality through software integration to support devops and CI/CD pipelines • Design, build, and operate cloud-based (AWS) data infrastructure, optimizing for scale, performance, and cost efficiency as the size of our data grows • Build frameworks and internal self-service tooling that helps the data team deliver value faster