Data Engineering Manager, Data Core - Fully Remote

LTK is experiencing explosive growth with exciting innovation in our roadmaps – driven by data and technology. As a Data Engineering Manager, you will be a technical manager within a growth-hungry, acceleration-minded team of problem-solvers and product-builders. We thrive in an extremely dynamic competitive environment, focusing relentlessly on the needs of our different customers (brands, creators, and consumers). We seek thought-partners who can collaborate effectively with engineering, product, and marketing teams to deliver quality solutions rapidly.

We are looking for a hands-on data engineering technologist who will lead a team of engineers to deliver the data engineering tooling and framework to optimize LTK’s data engineering delivery.  LTK’s Data Engineering Team delivers robust, reliable, and usable data pipelines and data sets that fuel our products, analytics, and data science solutions.

Responsibilities:

• Lead all aspects of continuous improvement initiatives (definition, analysis, architecture design, estimation) to optimize efficiencies, scale, and cost
• Participate in strategic direction of data engineering technology stack
• Stay abreast of data engineering technical trends and emerging approaches
• Evaluate new technologies and/or custom solutions
• Participate in building data engineering roadmap
• Define roadmap projects (“epics”) with clarity including scope, technical approach, and work estimations
• Facilitate on-time delivery of projects
• Effectively communicate and gain alignment both within team and with interdependent teams and stakeholders
• Manage all aspects of agile ceremonies (daily scrum, backlog grooming, sprint planning, retros, cross-squad alignment, etc.)
• Build and attract data engineering talent
• Cultivate a high performing engineering team
• Produce high quality technical documentation and artifacts that are easily consumable by data teams and other engineering teams

Qualifications

• Bachelor’s or Master’s degree in information systems, computer science, data engineering, analytics, or equivalent quantitative field
• Experience building production data pipelines, ELT/ETL solutions, data lakes, and data warehouses at a large scale
• 3+ years in a technology leadership role in data engineering
• 8+ years in data engineering on cloud data platform (min 5 years AWS)
• Programming proficiency in cloud data ecosystem using Python, R or Scala (min 5 years Scala)
• Highly proficient in engineering data pipelines using big data tooling (Spark, Hudi, Kafka)
• Highly proficient working in AWS cloud environment (S3, Cloud Formation, RDS, AWS Glue, Athena, EMR, Kinesis, Redshift)
• Exposure and experience with multiple platform stacks and tooling (Databricks, Snowflake, DBT, Airflow Orchestration, etc.)
• Strong understanding of cloud computing and optimization techniques
• 5+ years utilizing large scale Analytic/MPP data warehouse platform (Redshift, Snowflake, Vertica, etc.)
• Highly proficient with complex SQL
• Demonstrated leadership optimizing data pipeline engineering frameworks
• Demonstrated leadership and specialized expertise in the following:
• Batch data ingestion and processing
• Big data pipeline engineering and optimization
• Analytic/MPP data warehouse optimization
• Event streaming data processing

Preferred Qualifications

• AWS Certified Data Analytics - Specialty Certification
• Demonstrated leadership and specialized expertise in:
• Analytical data modeling
• Data pipeline metadata observability
• Data Platform Cost Optimization
• DataOps
• Specialized expertise designing and working with at least three (3) of the following data domains:
• Retail product data
• Ecommerce data
• Consumer profile data
• Clickstream data
• Consumer event data
• Marketing channel/campaign data
• Affiliate data
• Retailer/Brand data