Director of Data Engineering

Red Ventures

Director of Data Engineering leading engineering teams to build and scale data infrastructure at Red Ventures. Collaborating with business leaders to turn data into actionable insights.

Posted 7/17/2026full-timeRemote • North Carolina • 🇺🇸 United StatesLead💰 $190,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering teams to build scalable, real-time data pipelines using Spark and modern lakehouse platforms. Proficient in translating technical strategies to business priorities while ensuring high-quality data governance and team development.

Highest-signal resume keywords

Data Engineering LeadershipSpark Application DevelopmentAWS Data ServicesAgile MethodologiesCross-Functional Communication

ATS Keywords

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Hard Skills

SparkPythonScalaSQLSparkSQLSpark Structured StreamingDataFrame APIDistributed SystemsETL ProcessesData Pipeline Development

Soft Skills

Team DevelopmentCoachingCommunicationTrust BuildingCuriosity

Tools & Technologies

DatabricksAWSKinesisS3LambdaDynamoDBOracleSQL ServerPostgresMySQL

Industry Keywords

Data GovernanceReal-Time Data ProcessingData ProductsAgile PracticesData Lifecycle Management

Tech Stack

Tools & technologies

AWSDistributed SystemsDynamoDBETLMySQLOraclePostgresPythonScalaSparkSQL

About the role

Key responsibilities & impact

Lead a team of data engineers and engineering managers building large-scale, real-time data pipelines in Spark
Act as the primary technical liaison to business leadership, translating trade-offs between technology and business priorities in both directions
Set the multi-year technical direction for Data Engineering and communicate that strategy across both technical and business audiences
Partner with data scientists, analysts, and business stakeholders to turn business requirements into data products the team builds against
Represent Data Engineering in cross-functional and executive planning, building alignment across engineering, product, and business leaders
Set the architectural direction and standards for how data moves across platforms, from streaming ingestion through ETL to aggregation and analytics, hold your managers and teams accountable to that direction, and establish the engineering and agile practices that support delivery speed and quality
Stay close to the technical details to guide architecture design decisions, performance tuning, and tradeoff calls, and to give your team the context they need to move quickly without waiting on you
Work with your teams and the RV Data Platform team to design scalable solutions across distributed systems using AWS, Databricks, and modern big data technologies
Champion a governance-first mindset across your team, making sure the way we collect, move, and use data protects the privacy of the people behind it
Manage and develop the data engineering managers on your team, setting the bar for how they coach, hire, and run their teams
Own career development across your org, building growth paths for individual contributors and managers alike, and coaching through regular, direct feedback
Hold the team accountable for delivering high-quality, scalable solutions across the full data lifecycle

Requirements

What you’ll need

8-10 years of data or software engineering experience, including 5+ years managing engineering teams and at least 1 year managing managers
Track record of communicating technical strategy and tradeoffs clearly to non-technical executives, and building trust quickly with cross-functional peers
Deep curiosity about the systems and processes that produce our data, with enough understanding of the source to help your team strengthen and troubleshoot pipelines rather than treating data as a black box
Track record of leading engineering teams in an agile environment, coaching both engineers and managers, and giving teams enough context to operate independently
Deep hands-on experience building large-scale Spark applications for batch and streaming workloads
Experience with modern lakehouse platforms (Databricks or similar) in addition to traditional Spark-based pipelines
Expertise with the Spark RDD and DataFrame/Dataset APIs, with emphasis on DataFrames, for querying and data manipulation
Experience with Spark Structured Streaming and SparkSQL, including broadcast joins
Strong programming background in Python and/or Scala, with SQL fluency across large-scale datasets
Hands-on experience with AWS data services (Kinesis, S3, Lambda, DynamoDB)
Experience with ANSI SQL relational databases (Oracle, SQL Server, Postgres, MySQL)
Strong grounding in distributed systems and distributed data processing frameworks.

Benefits

Comp & perks

Health Insurance Coverage (medical, dental, and vision)
Life Insurance
Short and Long-Term Disability Insurance
Flexible Spending Accounts
Holiday Pay
401(k) with match
Employee Assistance Program
Paid Parental Bonding Benefit Program
Flexible Paid Time Off (PTO): We believe time to rest and recharge is essential. That’s why we offer a generous and flexible PTO policy. Full-time employees accrue 20 days of PTO for a full calendar year annually, with an increase to 25 days after five years of service.