IT - Database Developer

Aquent is partnering with a leading financial services institution that is at the forefront of leveraging data to drive intelligent planning and analytics. This organization is dedicated to empowering its teams with modern data products and AI-enabled analytical capabilities, fostering an environment where innovation and data-driven decisions thrive. Join us in making a significant impact on critical initiatives, shaping the future of financial technology, and contributing to a dynamic, forward-thinking environment.

About the Opportunity

We are seeking a highly skilled and hands-on professional to join our advanced analytics team. In this pivotal contract role, you will be instrumental in developing the cutting-edge data foundation for our Answer Engine Optimization (AEO) initiatives. You will design and build scalable data marts and automated pipelines within a robust cloud platform, directly contributing to the evolution of our digital marketing strategies and the insights we derive from them. This is an exciting chance to apply your deep data engineering expertise to create tangible, high-impact solutions that support reporting, advanced analytics, and future AI use cases, all while collaborating with a diverse team of technology partners.

What You'll Do

• Design and build scalable AEO data marts within a leading cloud platform.
• Develop automated pipelines for ingesting data from third-party AEO vendor APIs.
• Utilize Python to create reusable API integrations, extraction processes, and data transformation components.
• Manage complex API interactions including authentication, pagination, response processing, error handling, and logging.
• Create well-structured analytical data models to support reporting, analysis, and AI applications.
• Write complex SQL from scratch to transform, integrate, validate, and prepare AEO data.
• Integrate AEO vendor data with relevant digital marketing and core business datasets.
• Establish and maintain data quality checks, reconciliation processes, and monitoring.
• Document source structures, business rules, data grain, refresh frequency, dependencies, and transformation logic.
• Partner with internal technology teams to prepare data pipelines and products for production.
• Design maintainable, reusable, and observable solutions aligned with enterprise technology standards.
• Support the consumption of AEO data through business intelligence platforms, analytical workflows, and AI-enabled applications.
• Maintain, troubleshoot, and enhance an existing digital marketing data mart.
• Support data models integrating web analytics clickstream and web-traffic data with core business data.
• Write, review, troubleshoot, and optimize complex SQL.
• Develop reusable datasets for BI dashboards, recurring reporting, and ad hoc analytics.
• Evaluate source data, joins, table grain, business rules, refresh schedules, and downstream dependencies.
• Monitor data quality and resolve completeness, consistency, performance, and refresh issues.
• Update data models as reporting and analytical requirements evolve.
• Apply established standards for table design, column naming, audit fields, retention, and technical documentation.
• Partner with BI developers and analysts to ensure datasets are understandable, trusted, and fit for purpose.
• Improve the maintainability and scalability of existing SQL and data-processing workflows.
• Create clear technical documentation for data marts, pipelines, APIs, AI agents, and analytical datasets.
• Document solution architecture, data flows, source dependencies, business rules, configurations, ownership, and support procedures.
• Define source expectations such as data keys, grain, schema, refresh cadence, latency, and change-management considerations.
• Support code reviews, version control, testing, deployment preparation, monitoring, and issue resolution.
• Communicate technical risks, dependencies, decisions, and progress to both technical and non-technical stakeholders.
• Work collaboratively with technology, security, architecture, and production-support teams.

What You'll Bring

• Professional experience in data engineering, analytics engineering, software engineering, or a related technical field.
• Advanced SQL skills, including demonstrated ability to write complex SQL from scratch.
• Proficiency in Python for API integration, data extraction, automation, and transformation.
• Hands-on experience designing and building data pipelines and analytical data models.
• Experience integrating data from REST APIs or other third-party interfaces.
• Hands-on experience with Google Cloud Platform and cloud-based data services.
• Experience building data marts or other curated analytical data products.
• Knowledge of dimensional modeling, data grain, transformation logic, and reusable data assets.
• Experience with data-quality testing, validation, logging, monitoring, and exception handling.
• Experience using source control and collaborative development practices.
• Strong technical documentation and communication skills.
• Ability to work with business, analytics, engineering, architecture, and production-support partners.
• Ability to work independently and manage priorities across multiple related initiatives.

Bonus Points

• Experience building data products for Answer Engine Optimization, search analytics, digital visibility, content intelligence, or a related area.
• Experience working with third-party marketing or analytics vendor APIs.
• Experience with various web analytics platforms, clickstream data, web-traffic data, or other event-level digital behavioral data.
• Experience integrating digital marketing data with client, account, product, campaign, or other core business information.
• Experience developing AI agents from proof of concept into production.
• Experience with modern analytics-engineering technologies, including: dbt, dlt, and DuckDB.
• Working knowledge of modern AI capabilities, including LLM-based applications, retrieval-augmented generation, vector search and embeddings, AI tool-use patterns, agentic AI frameworks and orchestration, model and agent evaluation, and human-in-the-loop controls.
• Experience with business intelligence and analytics platforms such as Tableau, Looker, Power BI, or similar tools.
• Experience using GitHub Copilot in Visual Studio Code or comparable AI-assisted development tools.
• Familiarity with GitHub, pull requests, code reviews, CI/CD, and DevOps practices.
• Experience using Jira or a similar work-management platform.
• Experience presenting technical concepts, demonstrations, or engineering best practices to other teams.
• Previous experience in financial services or another highly regulated industry.

What Success Looks Like

• Delivering reliable and well-documented AEO data marts and automated API pipelines in a cloud environment.
• Maintaining a trusted digital marketing data mart that effectively supports business intelligence, reporting, and analytics.
• Producing reusable SQL, Python, documentation, and development patterns.
• Building effective working relationships across analytics and technology teams.

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About Aquent Talent:

Aquent Talent connects the best talent in marketing, creative, and design with the world's biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match.

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We're about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.