Data Ideology, LLC

Data Engineer

• Ability to collect and understand business requirements and translate those requirements into data models, integration strategies, and implementation plans.
• Lead modernization and migration initiatives to move clients from legacy systems into Snowflake, ensuring functionality, performance and data integrity.
• Ability to work within the SDLC framework in multiple environments and understand the complexities and dependencies of the data warehouse.
• Optimize and troubleshoot ETL/ELT workflows, applying best practices for scheduling, orchestration, and performance tuning
• Maintain documentation, architecture diagrams, and migration plans to support knowledge transfer and project tracking.

Senior Data Engineer, Healthcare

• Design and build scalable, secure, and cost-effective data solutions in Snowflake.
• Develop and optimize data pipelines using tools such as dbt, Python, CloverDX, and cloud-native services.
• Participate in discovery sessions with clients to gather requirements and translate them into solution designs and project plans.
• Collaborate with engagement managers and account teams to help scope work and provide technical input for Statements of Work (SOWs).
• Serve as a Snowflake subject matter expert, guiding best practices in performance tuning, cost optimization, access control, and workload management.
• Lead modernization and migration initiatives to move clients from legacy systems into Snowflake.
• Integrate Snowflake with BI tools, governance platforms, and AI/ML frameworks.
• Contribute to internal accelerators, frameworks, and proofs of concept.
• Mentor junior engineers and support knowledge sharing across the team.

Senior Data Engineer – Snowflake

Data Analyst

• Data Analysis and Interpretation: Conduct in-depth analysis using the data warehouse to identify trends, patterns, and insights. Interpret complex data sets and communicate findings to both technical and non-technical stakeholders.
• Data Extraction and Transformation: Assist with ETL processes to extract, transform, and load data from various sources. Collaborate with IT teams to create seamless data integrations.
• Quality Assurance and Testing Perform thorough data validation and testing to ensure the highest possible data quality. Clearly define and communicate when quality standards are not being met.
• Problem Solving Perform root cause analysis to identify the underlying or fundamental causes of an issue or problem. Demonstrate ability to offer suggestions and solutions to remedy issues and promote sustainability.
• Collaboration and Communication: Work closely with cross-functional teams, including IT and business stakeholders, to align on goals and key deliverables. Effectively prioritize tasks to meet established team goals.
• Documentation: Accurately document data mappings and definitions. Outline standard processes and procedures of core activities

• Develop production-ready data models by integrating multiple data sources.
• Collect and translate business requirements into actionable data warehouse plans.
• Work within the SDLC framework in multiple environments and manage complexities and dependencies of the data warehouse.
• Define and implement best practices across database design and ETL.
• Direct ETL development and apply ETL/ELT optimization and scheduling best practices.
• Collaborate with business and technical teams to ensure business requirements are fulfilled throughout the data & analytics lifecycle.
• Remote work from home; hours generally Monday through Friday with client-dependent business hours.

Senior Data Engineer

• Organize and manage deliverables in a data warehouse consolidation and business intelligence implementation project.
• Conduct in-depth analysis using the data warehouse to identify trends, patterns, and insights and communicate findings to technical and non-technical stakeholders.
• Assist with ETL processes to extract, transform, and load data from various sources and collaborate with IT teams to create seamless data integrations.
• Perform data validation, testing, and quality assurance; define and communicate when quality standards are not being met.
• Perform root cause analysis to identify underlying causes and propose sustainable solutions.
• Collaborate closely with cross-functional teams, including IT and business stakeholders, to align on goals and key deliverables.
• Accurately document data mappings, definitions, and standard processes and procedures of core activities.

Senior Data Analyst

• Collect and understand business requirements and translate those requirements into an actionable data warehouse plan
• Develop production-ready data models by integrating multiple data sources
• Leverage multi-dimensional and tabular design patterns and identify modeling solutions
• Work within the SDLC framework across multiple environments and manage complexities and dependencies of the data warehouse
• Define and implement best practices across database design and ETL
• Direct ETL development and demonstrate understanding of key ETL/ELT concepts, optimization, and scheduling
• Collaborate with business and technical teams to ensure business requirements are fulfilled throughout the data & analytics lifecycle

• Design and build scalable, secure, and cost-effective data architectures in Snowflake, aligned with industry and client best practices
• Implement data pipelines using ETL/ELT tools such as dbt, Python, CloverDX, and cloud-native services
• Conduct technical discovery sessions to understand client goals and translate them into architectural designs and project plans
• Collaborate with pre-sales and account teams to scope work, define solutions, and estimate effort for Statements of Work (SOWs)
• Serve as a Snowflake SME, providing guidance on performance tuning, cost optimization, access control, data sharing, and workload management
• Lead and execute data platform modernization and migration initiatives, moving clients from legacy systems to Snowflake-based solutions
• Integrate Snowflake environments with BI tools, data governance platforms, and AI/ML frameworks
• Contribute to internal IP, including templates, frameworks, accelerators, and proofs of concept (POCs)
• Support delivery engagements by implementing scalable solutions and continuously improving architectures based on business needs
• Mentor junior team members and contribute to ongoing knowledge sharing across the engineering team
• Hybrid pre-sales and delivery, client-facing consultative role

Senior Data Engineer, Snowflake

Data Ideology is seeking a Snowflake Data Engineer to support our growing partnership with Snowflake in a pre-sales and delivery hybrid role.
This position is a client-facing, consultative role that bridges the gap between technical strategy and practical implementation.
Design and build robust, scalable, and secure data architectures in Snowflake, aligned with industry and client best practices.
Implement ETL/ELT pipelines using tools such as DBT, Python, CloverDX, and cloud-native services.
Conduct technical discovery sessions and assessments to understand client requirements and translate them into solution designs.
Collaborate with pre-sales and account teams to scope work, define solutions, and estimate effort for Statements of Work (SOWs).
Serve as a Snowflake SME, advising on architecture, performance tuning, cost optimization, security, and workload design.
Partner with clients to modernize legacy data platforms and migrate to Snowflake-based data ecosystems.
Integrate with data visualization, governance, and AI/ML frameworks to support advanced analytics and business intelligence use cases.
Contribute to reusable assets such as templates, frameworks, reference architectures, and POCs.
Lead technical delivery for client engagements, supporting both implementation and ongoing solution refinement.
Mentor junior engineers and participate in internal knowledge-sharing and technical upskilling initiatives.
Remote work from home. Hours of work and days are generally Monday through Friday. Specific business hours will depend on client needs.

Data Engineer, Snowflake

Director

Director, Data Strategy & Practice Lead to build, grow, and lead our Data Strategy practice.
Define the strategic direction of Data Ideology’s Data Strategy practice.
Own end-to-end delivery of client engagements, from discovery through execution.
Translate complex business needs into frameworks and actionable deliverables (data strategy, analytics roadmaps, governance models).
Publish blogs, whitepapers, and frameworks showcasing Data Ideology’s expertise.
Build methodologies, models, and best practices for repeatable, high-value client delivery.
Mentor and coach team members across disciplines.
Support proposals, presentations, and scoping of new client opportunities.

Director, Data Strategy

Engineer

• Configure, deploy, and maintain F5 BIG-IP LTM, DNS, Web Application Firewall, and manage TLS/SSL certificates.
• Perform network and application troubleshooting, monitoring, alert management, and packet capture analysis.
• Develop Visio diagrams, end-user guides, and other technical documentation.
• Utilize Azure security services, automation tools, and container ingress services to enhance delivery performance and security.
• Maintain current knowledge of security techniques and technologies to mitigate risk.
• Communicate root cause analysis and resolutions effectively to stakeholders.
• Work Environment: Remote work from home.
• Hours of work and days are generally Monday through Friday. Specific business hours will depend on client needs.