Data Operations Manager
Oversee Enterprise Data Platform development and operations to acquire, ingest, and manage data from variety of Enterprise data sources. This will include partnering with data management capabilities across Koch. Dev/ops leader that oversees the growth and support of (Koch Industries, Inc.) KII’s Finance-Tax Enterprise Data Platform. As a key member of the leadership team this role contributes to the development and execution of the enterprise wide data strategy and is responsible for ensuring the platform and operating environment supporting this strategy are fully aligned, positioning the team to deliver compelling business value in support of data product teams across the enterprise.
What You Will Do In Your Role
- Build and lead a global data engineering team. Inspire and deliver data engineering innovations that fuel the growth of business; coach team members and grow the skill sets.; Mentor and guide team members as needed
- Work with data delivery teams to gather, understand, document, and prioritize requirements ensuring that the DataOps team backlog is refined and well understood by the team; Ability to influence across different groups and levels in the organization
- Provide technical leadership in data engineering practices. Partner with architecture, security, data delivery teams, data scientists and business leaders to establish a strong relationship and trust for prioritizing and delivering data products on time and with a high degree of quality
- Manage dependencies across data delivery teams to ensure alignment, as well as adjusting team directions when gaps exist
- Accountable for the design, build, and run of the data sourcing strategy to support downstream consumption across consumption methods (traditional BI and advanced analytics)
- Participate in Roadmap planning activities and Program Increment Planning of data product releases
- Manage production data pipelines and ensure SLAs are aligned to business needs
- Manage DataOps Team Capacity and resource allocation to optimize spend
- Participate in solution testing with stakeholders and development teams to ensure the integration solutions are working as expected and meeting all business objectives
- Prioritize backlog items across the DataOps team and allocate resources to meet business and data delivery team goals
- Partner with Architects to establish patterns for re-use, standards, and best practices for DataOps
- Process the data into clean, accessible sets in alignment with enterprise taxonomy standards
- Mature structured sandbox environment (e.g., test and learn zone) to support experimentation where appropriate
- Interface with other technology teams to ingest, process, and store data from a wide variety of data sources using cloud data technologies
- Creation and support of real-time data pipelines and querying capability leveraging enterprise standard technologies (e.g., Kafka/Kinesis/SQS, Glue, Spark, Redshift/Spectrum and Athena)
- Partner with the data governance teams and data management teams to establish authoritative sources for the core data elements required to support Business processes and reporting
- Recommend technology solutions to improve data quality and data integration across the enterprise data platform
- Implement the appropriate governance structure to prescribe data handling, protection, and user provisioning controls
- Partner with data governance teams to support operational activities related to data management such as metadata capture, data quality, data security, data lineage, data inventory
The Experience You Will Bring
- Bachelor's Degree with 2+ years in supervisory experience in building and leading data engineering teams
- At least 3 years of industry experience in building data engineering solutions: Ingestion, Curation, Modeling, Persistence, Computation and Delivery
- Proven Track record of guiding teams through unstructured technical problems to deliver business impact. Demonstrated Ability to translate high-level business objectives into actions. Must be able to reference specific work product in relation to these skills.
- At least 3 years experience at running cross-functional relationships and communicating with leadership across multiple organizations, departments, or capabilities
- Demonstrated understanding of Data Architecture, Data Integration, Data Quality, Data Governance, OLAP, Multi-Dimensional Modeling and Data Lineage concepts. Must be able to reference specific work product in relation to these skills
- At least 3 years experience in contributing to data governance and security in a data platform
- Demonstrated communication skills to collaborate with multiple Engineering, IT, and business teams. Must have worked in a matrixed environment and provide examples of communication strategy leveraged
- At least 2 years experience working in Agile environments supporting multiple product owners with competing priorities.
What Will Put You Ahead
- Demonstrated understanding of delivering data solutions and architecture using cloud services like SQS, Kinesis, S3, EMR, Spark, Athena, Redshift or Snowflake, ML Solutions, etc.
- Product management experience in Data Management areas (e.g. Data Governance/Data Quality/Data Integration, ETL, Big Data, Streaming Data) and/or equivalent experience as a Product Manager, Technical Lead, and has handled data from various sources (raw, transactional, real-time, streaming, etc.)
- Experience in Enterprise data projects (ingestion, pipeline, integration, etc.)
- Experience with the use of Statistical Process Control (SPC) to monitor and control the data analytics pipeline
- Experience working with a variety of database technologies.(e.g. relational, non-relational, timeseries, multi-dimensional…NoSQL, Postgres, Cassandra, MongoDB, Redshift or Snowflake, etc)
Salary and Benefits Commensurate with Experience.
Equal Opportunity Employer.
Except where prohibited by state law, all offers of employment are conditioned upon successfully passing a drug test.
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