Data Engineering Manager (Data Science & Analytics)

Los Angeles, California, United States

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Data Engineering Manager (Data Science and Analytics)

Los Angeles, CA (90024)

Tillster is seeking a strong leader for Data Engineering to own the delivery, storage, processing and reliable infrastructure of the Tillster Data Platform. As a Platform Lead, you will facilitate partnerships with other technical leads across the organization to set technical strategy, prioritize efforts, and foster a team dynamic that drives successful projects. As a people manager, you will find/create opportunities for your team members to grow in their roles and collaborate with other team members.  The ideal candidate for this role understands how to leverage their technical skills in order to help their team stay on the right track rather than become a technical bottleneck and can focus the team on projects that provide strategic value to the business in the long run.



  • Lead and support mappings of data sources, transformations, and data movement
  • Support data modeling and data warehouse analysis, architecture, design, and development, which includes but is not limited to, data collection/ingestion, redundant data storage, efficient processing and data manipulation, data modeling, data models/star schemas, and ETL/ELT processes
  • Providing expertise on dimensional modeling and database design best practices
  • Wrangle heterogeneous data and explore and discover new insights
  • Implement procedures and processes to validate data to ensure that data integrity and quality standards are met (and notify required parties when issues crop up)
  • Ensure all development, validation, data storage, and transformational processes follow internal SDLC and meet data compliance requirements such as CCPA, GDPR, and other certifications.
  • Solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions.
  • You should be well-oriented in Amazon EC2, AWS Lambda, Amazon S3, DynamoDB.
  • Build and grow a distributed team (US- and India-based) of hardworking and motivated engineers with an emphasis on ownership, throughput and leverage
  • Develop, mentor and motivate a team of Data Engineers to build, test and refine data processing and storage solutions
  • Foster a collaborative team culture that embodies both industry best practices and Tillster values
  • Work with engineering teams to understand and anticipate their current and future data needs, identifying scalable, self-service oriented solutions
  • Work with technical leads to set technical strategies and align/prioritize efforts
  • Manage daily operations of the team: create a focus on team priorities while effectively managing interrupt- driven work
  • Drive adoption of infrastructure and design patterns that align with company and technology goals
  • Foster an automation-oriented approach to solving problems, improving environment consistency and quality of life for on-call engineers


Required Skillset:

  • Bachelor’s degree in a quantitative area such as Math, Statistics, Computer Science, Engineering or equivalent experience
  • 5+ years of experience in data engineering or related field handling both structured and unstructured data, with heavy emphasis on providing the delivery, storage, processing and reliable infrastructure of data
  • Strong knowledge of the AWS data ecosystem (S3, EMR, Athena, Spark, etc.)
  • Experience with or solid understanding of data pipelines and event-driven architectures (Kinesis, Kafka)
  • Deep knowledge of, and experience with, traditional data warehousing models, practices, and processes
  • Strong understanding of ELT/ETL Design Patterns, best practices, and tooling
  • Wide knowledge of data visualization and analytics tools (Tableau, Looker, Qlik, etc.)
  • 3+ years with distributed data warehousing systems such as Redshift or Snowflake,
  • Proficiency in Python or related scripting languages
  • Experience growing and managing teams, with an emphasis on cohesion and throughput
  • Ability to thrive in a dynamic and fast-paced operational environment, inspire change, and collaborate with a variety of teams and organizational partners
  • Highly motivated self-starter with bias to action and passion for delivering high-quality data solutions
  • Attention to detail and quality with excellent problem solving and communication skills
  • Working knowledge of agile development processes


Nice to haves:

  • Advanced degree in a quantitative area such as Math, Statistics, Computer Science, Engineering or equivalent experience
  • Experience with Looker (developing data pipelines and optimizing data delivery for Looker)
  • Experience in data processing using Snowflake or DBT
  • Experience consuming and integrating third-party event data sources such as Google Analytics,, social media feeds, etc.
  • Deep understanding of CI/CD methodologies with an emphasis on the creation of tooling and automation
  • Additional knowledge of other stats-oriented scripting languages such as R or statistical software (SPSS, RapidMiner, etc.) helpful.
Job region(s): North America
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