Flow Traders
DataEngineeringManager
Neural analysis suggests this role is
optimal for Senior candidates.
“Data Engineering Manager at Flow Traders. Skills: Data Platform evolution, Core Data maintenance, Business Intelligence delivery, Data governance implementation, People management, Team scaling, Operational excellence. Define and maintain roadmaps for Data Platform, Core Data, and BI. Champion platform and data product thinking”
What You'll Achieve.
Align data priorities with business goals; Increase adoption and reduce operational load; Timely, high-quality delivery of software, datasets and reports; Meet SLAs for intraday and end-of-day pipelines; Ensure appropriate handling of sensitive trading data
Industry & Context.
On-call, Incident management
What They're Looking For.
Must Have
3+ years of engineering management leading data/platform and/or analytics engineering teams, 8+ years total in data/platform/analytics engineering, Demonstrated success growing data engineers’ careers, improving team health, and leading multi-squad delivery, Tooling familiarity across at least one modern data engineering stack, Proven track record delivering against roadmaps and tight SLAs for mission-critical data, including on-call and incident management, Experience scaling a data platform grasp of non-functional requirements (storage/compute architecture, performance, reliability, security, and cost), Familiarity with data governance practices (catalog/lineage, access controls, retention/auditability, data quality frameworks), stakeholder management and communication, comfortable working with trading, research, risk, finance, and compliance
Nice to Have
Google Cloud Platform (GCP): Big Query, Pub/Sub, Dataflow, Dataproc, Cloud Composer, GKE, Cloud Storage, IAM/VPC; cost management and workload isolation on GCP, Familiarity with at least one management reporting tool like Power BI, Tableau, Trading industry experience: market data ingestion, quantitative research workflows (e. g. model training, back testing), order/execution and risk data, PNL, familiarity with regulatory reporting
What You'll Do.
Define and maintain roadmaps for Data Platform
Champion platform and data product thinking
Manage project priorities
dependencies and risks
Establish operational rituals
Drive operational excellence
Own career development
Build and scale the team
Foster a culture of innovation
and continuous learning
Run effective team practices
Domain accountability across the data organization
self-serve data platform
Lead teams building and maintaining critical datasets
Deliver trustworthy KPIs
semantic models/metrics layers
Set and meet SLAs for intraday and end-of-day pipelines
Partner with Security
and Compliance on data governance
How You'll Work.
Team & Collaboration
Partner with other technology teams like quantitative research, trading, risk, finance and compliance; Align data priorities with business goals; Work with trading, research, risk, finance, and compliance stakeholders
Communication Scope
Stakeholder management and communication; Communicate with trading, research, risk, finance, and compliance
Process & Methodology
Manage project priorities, dependencies and risks, Ensure timely, high-quality delivery of software, datasets and reports, Establish operational rituals like quarterly / iterative planning, change management, release practices and delivery reviews
Full Job Description
Flow Traders is looking for a Data Engineering Manager to lead the data department in our Amsterdam office and partner with other technology teams like quantitative research, trading, risk, finance and compliance to align data priorities with business goals. In this role you will define and maintain roadmaps for Data Platform, Core Data, and BI aligned to our company’s priorities and translate our objectives into milestones, as well as champion platform and data product thinking (clear interfaces, documented contracts and self-serving capabilities that increase adoption and reduce operational load). You will manage project priorities, dependencies and risks ensuring a timely, high-quality delivery of software, datasets and reports and you will establish operational rituals like quarterly / iterative planning, change management, release practices and delivery reviews. Overall, you will drive operational excellence when it comes to incident response, blameless postmortems, runbooks and continuous improvement. What you will do: People management and team success: Own career development, coaching, growth plans, performance reviews, and promotions Build and scale the team: hiring, headcount planning, on-boarding, resource allocation, and vendor management Foster a culture of innovation, ownership, and continuous learning Run effective team practices: 1:1s, team meetings, feedback cycles, and team-buildings Domain accountability across the data organization: Data Platform: evolve a scalable, self-serve platform (batch and streaming) with strong non-functional posture, storage/compute capacity planning, performance, reliability, security, disaster recovery, and cost efficiency Core Data (foundational datasets): lead teams building and maintaining critical datasets (market/reference data, orders/executions, risk), with robust modeling, schema evolution, idempotent processing, and reproducibility for both batch and streaming Business Intelligence: deliver trustworthy KPIs, s
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