Data Engineering Team Lead

Datasite

Data Engineering Team Lead building Grata’s private-market data platforms and analytics. Leading engineers, lakehouse architecture, streaming reliability, governance, and cross-functional delivery.

Posted 8/4/2026full-timeNew York City • New York • 🇺🇸 United StatesSenior💰 $141,000 - $248,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and mentoring Data Engineers while setting architectural standards for ELT/ETL pipelines using Python, SQL, and Spark. Proven ability to drive data modeling, performance management, and collaboration across teams to enhance data systems.

Highest-signal resume keywords

Data Engineering LeadershipPython ProficiencySQL ExpertiseSpark and Databricks KnowledgeAWS Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingELT/ETL Pipeline DesignDimensional ModelingIncremental Data PatternsAutomated TestingAnomaly DetectionCI/CD for DataInfrastructure as CodePerformance ManagementCareer Development

Soft Skills

Team ManagementMentoringFeedback DeliveryGoal-SettingCollaboration

Tools & Technologies

DatabricksAirflowDatabricks WorkflowsDbtMonitoring Tools

Industry Keywords

Lakehouse PatternsStreaming DataEvent-Data JobsSLOsCost Management

Tech Stack

Tools & technologies

AirflowAWSCloudETLPythonSparkSQL

About the role

Key responsibilities & impact

Manage and grow a team of Data Engineers, including goal-setting, 1:1s, feedback, hiring, and performance management
Set architecture and design standards for ELT/ETL pipelines using Python, SQL, Spark, and Databricks
Make build-vs-buy and platform trade-off decisions
Drive dimensional modeling, star schemas, and incremental data patterns across the lakehouse and warehouse
Set technical standards for streaming and event-data jobs, idempotency, and exactly-once semantics
Ensure automated testing, anomaly detection, validation, lineage, metadata, and documentation
Own SLOs and on-call rotations for data platforms
Scale monitoring, alerting, capacity, and cost management
Build roadmaps, sequence delivery, and drive measurable improvements in data freshness, completeness, and query performance
Partner with Product, Data Science, and Application Engineering on source selection, feature readiness, experiment design, APIs, and semantic layers
Lead design and code reviews, run brown-bag sessions, and coach engineers

Requirements

What you’ll need

6+ years building and operating production data systems at scale
Prior experience leading a team or mentoring senior engineers
Experience managing people or leading ambiguous, high-stakes initiatives to clear results
Experience with hiring, performance management, and career development
Deep fluency with Python and SQL
Expert knowledge of Spark, Databricks, and lakehouse patterns
Strong data modeling skills
Experience running workloads in AWS or a similar cloud, including storage, compute, networking basics, and cost controls
Hands-on experience with Airflow, Databricks Workflows, or dbt
Experience with CI/CD for data and infrastructure as code
Ability to operate as both an individual technical contributor and a people manager

Benefits

Comp & perks

Health insurance (medical, dental, vision)
Retirement savings plan
Paid time off
Other employee benefits
Potential eligibility for bonuses, commissions, or overtime if applicable