Sr. Data engineer
Job Attributes

Job Description
Title: Senior Data Engineer
Type: Fulltime permanent
Location: New York, NY / Fairfax, VA
Must Have:
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”.
Description
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.
Responsibilities:
• 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.
Requirements:
• 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.