Senior Data Engineer

About the opportunity

The Role As a Senior Data Engineer (B2B), you will own the development, maintenance, and evolution of data pipelines supporting Wpromote’s B2B clients and capabilities. You will work across client teams, Data Engineering, and Product to translate complex B2B marketing and business requirements into reliable, scalable data solutions. This role will spend approximately 75–85% of its time supporting B2B client data needs, with the remaining time focused on improving and standardizing our broader B2B data capabilities. You will own B2B data pipelines end-to-end, including implementing approved modifications to downstream pipelines and data models when necessary to meet client requirements. This role also owns the data layer for measurement and scoring programs. Measurement methodology and analysis design are owned by strategy and analytics partners, with this role building the datasets, pipelines, and validation tooling that support them. You will be expected to understand how changes flow through the broader data ecosystem, evaluate their impact, and implement solutions that preserve data quality and maintainability. As you identify common requirements across B2B clients, you will help turn those patterns into standardized models, reusable components, and scalable B2B data capabilities that reduce repeated custom development. At Wpromote, we believe that great work is only possible with great people. Our goal is to build a better, more inclusive work environment and support our people at every stage of their careers by prioritizing a strong work-life balance through our policies and benefits listed below. As a Best Place to Work according to both Ad Age and Glassdoor and Adweek’s Fastest Growing Digital Agency, we are moving fast to expand our teams and bring new experts into the fold to keep pushing the boundaries of what’s possible in marketing. We offer: -Remote-first culture -Unlimited PTO -Extended Holiday break (Winter) -Flexible schedules -100% paid parental leave -401(k) matching -Medical, Dental, Vision, Life, Pet Insurance -Sponsored life insurance -Short Term Disability insurance and additional voluntary insurance -Annual Class Pass credits and more! The anticipated annual salary for this role will range from $105,000-$135,000, based on consideration of a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, education and certifications, competitive benchmarks, scope of responsibility, market dynamics, geographic location, and respective state’s salary threshold for exempt employees. The total compensation package for this role will include benefits (listed above). *This position may be performed remotely in most states within the US, with some exclusions **While this role offers the flexibility to work remotely, we have office hubs in Los Angeles, Chicago, and New York, where you can join in on learning and development opportunities, fun events, take advantage of a space to work, and collaborate in person! ***This position is not eligible for immigration sponsorship Important Notice: Beware of Job Scams Wpromote recruiting communications will only be sent through our official channels via wpromote.com email addresses. If you see a posting elsewhere that is not reflected on Wpromote.com/careers, it may be a fraudulent posting. We do not require payment or fees during the hiring process nor do we request sensitive information, such as Social Security numbers or payment details. Please safeguard yourself against possible scams and contact us if you encounter any suspicious activity. #LI-JJ #LI-Remote You Will Be Owning the design, development, deployment, and ongoing support of data pipelines for Wpromote’s B2B clients using BigQuery, dbt, Python, and orchestration frameworks. Partnering with client teams and technical stakeholders to translate B2B marketing, sales, measurement, and reporting requirements into reliable data solutions. Managing client-specific requirements throughout the data lifecycle, including making approved modifications to downstream pipelines, transformations, and data models when required. Integrating and normalizing data across the B2B technology ecosystem, including CRM, marketing automation, ABM and intent, attribution, enrichment, sales engagement, paid media, web analytics, and first-party product usage and telemetry data. Building data models that connect anonymous and known engagement, leads, contacts, accounts, campaigns, opportunities, marketing touchpoints, and sales activity to support account-level measurement from initial engagement through pipeline and revenue. Understanding upstream and downstream dependencies, troubleshooting complex production issues, and ensuring changes maintain data quality, reliability, and scalability. Strengthening data quality through automated testing, validation, reconciliation, monitoring, and observability. Identifying recurring requirements across B2B clients and converting them into reusable models, frameworks, and configuration-driven solutions. Contributing to Wpromote’s standard B2B data architecture, including common approaches to account resolution, lifecycle stages, funnel definitions, and marketing-to-revenue measurement while maintaining flexibility for client-specific requirements. Using AI-assisted development tools to accelerate development, debugging, testing, documentation, and codebase exploration while maintaining accountability for production code. Building activation pipelines that push data back out to operational systems, including syncing account segments, scores, and lifecycle stages to ad platforms, writing enriched data and tasks back to CRM, and keeping platform audiences current with warehouse state. Investigating and validating the behavior of third-party and vendor data feeds, including delivery cadence, restatement, retention, and schema semantics, and designing pipelines that remain correct when feeds behave differently than documented. Building analytical datasets that support scoring model calibration and validation, such as regression inputs from CRM history, holdout construction, lift analysis, and feedback loops from sales dispositioning. You Must Have Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience. 5+ years of experience in data engineering, analytics engineering, or a related field, with experience independently owning production data pipelines and data models. Advanced proficiency in SQL and BigQuery, along with intermediate to advanced programming skills in Python. Strong experience with dbt or an equivalent transformation and orchestration framework including data modeling, testing, documentation, and reusable development patterns. Strong understanding of data warehousing, dimensional modeling, data transformation, and data quality principles. Hands-on data engineering or analytics experience with CRM and at least two other areas of the B2B technology ecosystem, such as marketing automation, ABM/intent, attribution, or paid media platforms. Strong understanding of B2B data models and customer journeys, including lead/contact-to-account relationships, lifecycle and funnel stages, opportunity and pipeline data, campaign membership, marketing touchpoints, and the challenges of connecting marketing activity to revenue. Experience integrating data across multiple B2B systems and reconciling differences in identifiers, entities, lifecycle definitions, business processes, and data structures. Strong problem-solving and communication skills, including the ability to navigate ambiguous client requirements, evaluate technical tradeoffs, and communicate solutions to technical and non-technical stakeholders. Experience within an advertising agency, consulting organization, or other multi-client environment. Experience with lead-to-account matching and identity resolution, including reconciling person-level and account-level data across systems. Experience reconstructing historical state from CRM and marketing data, such as lifecycle and opportunity stage history, snapshot-based feeds, and changes in account ownership or campaign membership over time. Nice to Have Experience with platforms across the B2B ecosystem, including: CRM & Sales: Salesforce Sales Cloud, HubSpot Marketing Automation: Marketo, Pardot (Marketing Cloud Account Engagement), Eloqua ABM & Intent: 6sense, Demandbase B2B Measurement & Attribution: Octane11, Adobe Marketo Measure (formerly Bizible) Data Enrichment & Prospecting: ZoomInfo Sales & Conversational Engagement: Salesloft, Qualified, Drift Content & Buyer Engagement: PathFactory Experience with multi-touch attribution and sourced/influenced pipeline measurement, including per-opportunity attribution models and credit window logic. Experience building B2B measurement models that connect marketing activity and media investment to account engagement, opportunities, pipeline, and revenue. Experience working with historical CRM and marketing data, including changes in lifecycle status, opportunity stages, campaign membership, account ownership, and other business events over time. Experience building reusable or configuration-driven data pipelines that support multiple clients while allowing controlled client-specific customization. Experience with data observability, lineage, metadata management, or data quality platforms. Familiarity with orchestration technologies such as Airflow, Dagster, AWS Glue, or Azure Data Factory, along with modern software engineering practices including Git, code review, CI/CD, and testing. Experience with audience syndication and reverse ETL patterns, including platform audience APIs (DSP, LinkedIn, Meta) or tools such as Hightouch or Census. Experience managing BigQuery cost and performance across multiple clients, including partitioning, clustering, and query cost discipline. Hands-on experience using AI-assisted software engineering tools such as Claude Code, OpenAI Codex, OpenCode, Cursor, GitHub Copilot, or similar tools, with the engineering judgment to review, test, and validate AI-generated solutions. What Success Looks Like Success in this role will center around three areas: Client Ownership: You will become a trusted technical owner for Wpromote’s B2B data pipelines, independently translating complex client requirements into reliable solutions and confidently managing changes across upstream and downstream systems. Quality: You will improve the reliability of our B2B data through stronger testing, validation, monitoring, documentation, and observability, while proactively identifying and addressing recurring data issues. Scale: You will recognize common patterns across B2B clients and help turn them into standardized, reusable capabilities, reducing repeated custom development while preserving the flexibility needed to support meaningful client-specific requirements. Wpromote is committed to bringing together individuals from different backgrounds and perspectives, providing employees with a safe and welcoming environment free of discrimination and harassment. We strive to create a diverse & inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together. As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family or parental status, disability*, age, veteran status, or any other status protected by the laws or regulations in the locations where we operate. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our workplace. Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Wpromote. This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9. For more information on E Verify, or if you believe that your employer has violated its E-Verify responsibilities, please contact DHS. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Responsibilities

• , please contact DHS.
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
• These tools assist our recruitment team but do not replace human judgment.
• Final hiring decisions are ultimately made by humans.
• If you would like more information about how your data is processed, please contact us.

Qualifications

• into reliable, scalable data solutions.
• This role will spend approximately 75–85% of its time supporting B2B client data needs, with the remaining time focused on improving and standardizing our broader B2B data capabilities.
• You will own B2B data pipelines end-to-end, including implementing approved modifications to downstream pipelines and data models when necessary to meet client
• This role also owns the data layer for measurement and scoring programs.
• Measurement methodology and analysis design are owned by strategy and analytics partners, with this role building the datasets, pipelines, and validation tooling that support them.
• You will be expected to understand how changes flow through the broader data ecosystem, evaluate their impact, and implement solutions that preserve data quality and maintainability.
• As you identify common
• across B2B clients, you will help turn those patterns into standardized models, reusable components, and scalable B2B data capabilities that reduce repeated custom development.