This job offer is no longer available
About
As a Senior Engineer, you'll work across a dynamic client roster finding, extracting, loading, and transforming data foundational to analysis and marketing decisions. You'll be responsible for collaboration with other key analytics positions to provide an end-to-end view of measurement and performance for clients. This role is fast-paced, collaborative, and ever-evolving: the right place for someone who wants to make an impact quickly and help shape the way data powers marketing decisions. What You'll Do Build and maintain data pipelines
Automate reporting pipelines with speed, accuracy, and scalability in mind. Demonstrate best practices in data engineering and account for considerations specific to media and site data in every step of the automation process. Write and optimize SQL views, Python/R scripts, and API connectors as needed. Continually optimize data cleaning and anomaly detection processes. Help manage and advance our GCP infrastructure, particularly with BigQuery and GCP integrations.
Own data quality and governance
Enforce naming conventions, dataset groupings, versioning, and access standards. Maintain rigorous QA practices to ensure clean, reliable, and consistent data. Continuously seek opportunities to improve processes and infrastructure.
Problem solve relentlessly
Proactively catch and investigate issues, finding root causes and going beyond surface solutions. Work with analysts to anticipate needs and ensure data is easy to find and use. Demonstrate situational awareness, knowing when to escalate, push or pull back, or execute. Communicate effectively with less technical stakeholders to address challenges and keep them updated on progress.
Contribute to strategy
Help shape the roadmap for our data architecture and processes. Identify opportunities to simplify, improve, and standardize workflows. Occasionally support client conversations with technical expertise.
You could be a good fit if: You take ownership of data quality and availability like it's mission critical. You already are, or have the drive to become, an expert in media data. You're a problem solver who doesn't stop at "it's broken." You figure out why and how to fix it. You balance speed and accuracy, knowing both matter in a client-driven environment. You're adaptable, resourceful, and curious. You're able to figure things out with limited direction. Learning new things and finding creative solutions are some of your favorite parts of your job. Requirements Education:
A bachelor's degree preferred or equivalent work experience in related field such as Computer Science, Data Science, Mathematics/Statistics, Marketing Analytics, etc. Skills and Experience:
4-8 years in data engineering, devops, data science, or similar. Experience in marketing or at an advertising agency preferred. Fluency in SQL and Python required. Additional competency in 1-2 other languages such as R, C/C++, C#, Java, Go, Rust, etc. preferred. Deep experience with GCP/GBQ or similar cloud platforms and data warehouses. Knowledge of ad tech and understanding of core media and site platforms (e.g., CM360, TTD, Google Ads, Google Analytics 4, Adobe analytics, etc.). Experience with dashboarding tools (e.g., Tableau, Looker, PowerBI, etc.) a plus.
Competencies (characteristics and work style):
Strong independent problem-solving skills. Adaptable to rapidly changing needs, situations, and priorities. Results-oriented with the ability to work well under pressure, effectively manage multiple projects simultaneously, and consistently meet deadlines. Able to communicate complex concepts in digestible ways to non-technical stakeholders.
The salary range for this position is listed below. Where an employee or prospective employee is paid within this range will depend on a variety of factors, including but not limited to budget, relevant experience, qualifications, and tenure in similar roles. Consideration may also be given to internal salary data for current or former employees in the same or similar positions. Salary Range: $105,000 - 135,000 annually
Nice-to-have skills
- Data Warehousing
- GCP
- Python
- SQL
Work experience
- Data Engineer
- Data Infrastructure
Languages
- English
Notice for Users
This job was posted by one of our partners. You can view the original job source here.