Sr. Data engineer
Title: Senior Data Engineer
Type: Fulltime permanent
Location: New York, NY / Fairfax, VA
1) Cloud Tech (Google Cloud Big Query, Snowflake), AWS + Snowflake will work if no google cloud exp.
2) Datawarehouse concepts
Other tech skillsets: reporting, SQL + Python
“US citizens and Green Card Holders and those authorized to work in the US are encouraged to apply. We are unable to sponsor H1b candidates at this time”.
Client is seeking an enthusiastic and experienced Senior Data Engineer to lead the team building cutting edge Ad Tech Data products in Delivery, Forecasting, Campaign Management and Reporting. Part of the growing Data & Product development team, the candidate should have experience defining the data strategy and roadmap, creating implementation goals and working with the internal and external teams to execute on the strategy. A successful candidate applies his/her expertise in state-of-the-art digital technologies, cloud data architecture, modern data warehouses and is relied on by top management to serve as a proxy for the market.
This person is a multi-tasker with attention to detail, who is comfortable being the go-to expert for Digital Ad-Tech. He/She is obsessive about customer needs and can create a collaborative work environment to address those needs; makes decisions based on data and involving all areas of the business as part of the product development lifecycle.
• Oversees and directs the work of Ad Tech Data Support Specialist and Business Analyst/ Project Lead positions, including creating an ongoing training and development plan.
• Define, prioritize, and maintain client tactical roadmap for our customer facing applications, in alignment with our strategic vision.
• Daily Interactions with senior management to keep abreast of objectives.
• Serve as the domain expert for your area, with a deep understanding of the ad tech landscape, its table stakes, as well as how can differentiate.
• Authors requirements and user stories in conjunction (with stakeholders as necessary) ensuring that market needs are met. Ensures documentation of requirements and business logic are accounted for and up-to-date.
• Creates buy-in for the Data & Insights vision, both internally and with key external partners; Manage prioritization and trade-offs among all stakeholders.
• Proactively identify, troubleshoot and resolve strategic issues that may impair the team’s ability to meet technical or strategic goals.
• 5+ years of experience designing, architecting & implementing data warehouse solutions.
• Has an affinity towards large datasets, an inherent ability to observe trends and draw actionable insights from the same.
• Hands on experience on Cloud data warehouses preferably on Snowflake/Google Big Query.
• Hands on experience with any of the Cloud technologies like GCP, AWS, Azure
• 5+ years on experience in writing complex SQL queries, ETL/ELT pipeline development and Reporting development.
• 2+ years of experience in programming languages preferably in Python.
• 2+ years of experience in reporting development preferably in Tableau/Google Data Studio.
• Experience managing an agile design driven, user-centered data and development team.
• Proven ability to partner effectively across functions, with an exposure to complex organizations and the ability to gain shared vision on data product decisions and priority trade-offs.
• Excellent communication skills, both verbal and written, with meticulous attention to detail. Ability to communicate technical issues simply to help drive fast decisions.
• Deep experience with identity, data privacy, audience targeting, cross-device graphs and related technologies.
• Advanced knowledge of digital advertising technology not just limited to ad serving, analytics, DSP, DMP, SSP, QA, and targeting.
• Has hands-on experience working with tools and systems that are instrumental at various stages of digital ad campaigns.
• Preferably has knowledge on implementing and testing third party tags across video platforms. Utilizing customer driven design and development and lean startup methodologies, have a fail fast mindset.
• A fast learning curve, with the ability to understand our customer’s needs on both a business and technical level.
• Travel (no more than 5%) to sales/client meetings to gather feedback on existing data products and new features to be included in the roadmap.