Job description

Our Client, an IT Services and Consultant company, is looking for a Senior Data Engineer – Snowflake & dbt / Data Modeling for their Blaine, MN/Hybrid location. Responsibilities: • Drive end to end design of robust conceptual logical and physical data models that support cross functional analytics use cases and complex reporting needs for global stakeholders. • Architect and implement scalable data pipelines using data build tool to transform integrate and validate diverse data sources into trusted Snowflake environments aligned with business objectives. • Optimize Snowflake schemas storage patterns clustering strategies and query performance to ensure efficient resource usage and consistently fast response times for critical workloads. • Collaborate closely with data engineers analysts and product teams to translate business requirements into precise data design specifications and maintain shared understanding of data definitions. • Establish and enforce data modelling standards naming conventions and documentation practices that enhance long term maintainability and onboarding efficiency across the data ecosystem. • Design and implement robust data quality checks data build tool tests and reconciliation routines that proactively detect anomalies and protect downstream consumers from inaccurate information. • Integrate Snowflake with upstream and downstream tools including orchestration platforms and analytics applications to create seamless data flows and reduce manual intervention in day to day operations. • Analyze existing data implementations to identify technical debt bottlenecks and improvement opportunities then propose and execute remediation plans that elevate reliability and usability. • Partner with security and compliance teams to embed data governance principles access controls and audit capabilities into models and pipelines ensuring responsible use of enterprise data assets. • Provide detailed technical guidance and mentoring to peers on data modelling patterns data build tool usage and Snowflake best practices thereby uplifting overall team capabilities and solution quality. • Coordinate deployment activities across hybrid work arrangements ensuring stable releases in Snowflake environments and timely resolution of issues discovered during testing and production use. • Document data models lineage transformation logic and operational workflows in a clear and structured manner so that teams across the organization can confidently leverage shared data products. • Contribute to continuous improvement initiatives by evaluating emerging features in data build tool and Snowflake and recommending pragmatic adoption paths that deliver measurable business value. Requirements: • Demonstrate extensive experience in enterprise scale data modelling including dimensional modelling normalized structures and data vault approaches applied to complex analytical platforms. • Show strong hands on expertise with data build tool for developing modular transformation code managing environments implementing testing and orchestrating reliable deployment workflows. • Apply deep practical proficiency in Snowflake capabilities such as virtual warehouses micro partitioning time travel and role based access to design efficient and secure data solutions. • Bring solid understanding of cloud data architectures data integration patterns and performance tuning techniques that are relevant for modern hybrid analytics ecosystems. • Exhibit proficiency in structured query design and optimization along with familiarity in scripting for automation to streamline recurring data management activities. • Possess experience working in hybrid work models using collaborative tools and practices that maintain clear communication documentation and alignment across distributed teams. • Hold exposure to agile delivery methods and backlog management enabling effective prioritization of data features and transparent progress reporting to stakeholders. • Display strong problem solving capabilities with a track record of diagnosing complex data issues and proposing practical solutions that improve trust in analytical outputs. • Maintain awareness of data governance privacy and regulatory considerations and incorporate these aspects into everyday design decisions and implementation patterns. • Present excellent communication skills to explain technical data concepts in accessible language and support informed decision making by business and technology partners. • Bring prior experience in large scale MNC or similar environments where coordination across multiple domains and systems is necessary to deliver integrated data solutions. • Commit to ongoing learning of new data platform features modelling approaches and automation practices ensuring that solutions remain current with industry developments. • Experience: 10 Yrs Why Should You Apply? • Health Benefits • Referral Program • Excellent growth and advancement opportunities

Requirements

Must-haves

Our Client, an IT Services and Consultant company, is looking for a Senior Data Engineer – Snowflake & dbt / Data Modeling for their Blaine, MN/Hybrid location.
Drive end to end design of robust conceptual logical and physical data models that support cross functional analytics use cases and complex reporting needs for global stakeholders.
Architect and implement scalable data pipelines using data build tool to transform integrate and validate diverse data sources into trusted Snowflake environments aligned with business objectives.
Optimize Snowflake schemas storage patterns clustering strategies and query performance to ensure efficient resource usage and consistently fast response times for critical workloads.
Collaborate closely with data engineers analysts and product teams to translate business requirements into precise data design specifications and maintain shared understanding of data definitions.
Establish and enforce data modelling standards naming conventions and documentation practices that enhance long term maintainability and onboarding efficiency across the data ecosystem.
Design and implement robust data quality checks data build tool tests and reconciliation routines that proactively detect anomalies and protect downstream consumers from inaccurate information.
Integrate Snowflake with upstream and downstream tools including orchestration platforms and analytics applications to create seamless data flows and reduce manual intervention in day to day operations.
Analyze existing data implementations to identify technical debt bottlenecks and improvement opportunities then propose and execute remediation plans that elevate reliability and usability.
Partner with security and compliance teams to embed data governance principles access controls and audit capabilities into models and pipelines ensuring responsible use of enterprise data assets.
Provide detailed technical guidance and mentoring to peers on data modelling patterns data build tool usage and Snowflake best practices thereby uplifting overall team capabilities and solution quality.
Coordinate deployment activities across hybrid work arrangements ensuring stable releases in Snowflake environments and timely resolution of issues discovered during testing and production use.
Document data models lineage transformation logic and operational workflows in a clear and structured manner so that teams across the organization can confidently leverage shared data products.
Contribute to continuous improvement initiatives by evaluating emerging features in data build tool and Snowflake and recommending pragmatic adoption paths that deliver measurable business value.
Demonstrate extensive experience in enterprise scale data modelling including dimensional modelling normalized structures and data vault approaches applied to complex analytical platforms.
Show strong hands on expertise with data build tool for developing modular transformation code managing environments implementing testing and orchestrating reliable deployment workflows.
Apply deep practical proficiency in Snowflake capabilities such as virtual warehouses micro partitioning time travel and role based access to design efficient and secure data solutions.
Bring solid understanding of cloud data architectures data integration patterns and performance tuning techniques that are relevant for modern hybrid analytics ecosystems.
Exhibit proficiency in structured query design and optimization along with familiarity in scripting for automation to streamline recurring data management activities.
Possess experience working in hybrid work models using collaborative tools and practices that maintain clear communication documentation and alignment across distributed teams.
Hold exposure to agile delivery methods and backlog management enabling effective prioritization of data features and transparent progress reporting to stakeholders.
Display strong problem solving capabilities with a track record of diagnosing complex data issues and proposing practical solutions that improve trust in analytical outputs.
Maintain awareness of data governance privacy and regulatory considerations and incorporate these aspects into everyday design decisions and implementation patterns.
Present excellent communication skills to explain technical data concepts in accessible language and support informed decision making by business and technology partners.

Nice-to-haves

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Keywords to mirror

agile

Platform: jobdiva
Effort: medium