The Data Engineer is responsible for developing and maintaining data pipelines to support data ingestion, transformation, and integration within a scalable data platform. This role ensures that data from multiple sources is processed efficiently, securely, and with high quality standards. Responsibilities - Develop and maintain data ingestion pipelines from multiple sources - Build ETL/ELT processes for data transformation - Integrate structured and unstructured data into data platforms - Implement incremental and automated data ingestion processes - Ensure data quality through validations and monitoring - Perform data cleaning and normalization tasks - Optimize pipelines for performance and scalability - Document data pipelines and data structures - Collaborate with cross-functional teams to support data initiatives Requirements - Bachelor’s degree in Computer Science, Engineering, or related field - Experience in data engineering or data pipeline development - Knowledge of ETL/ELT processes and data integration concepts - Experience with cloud-based data platforms (AWS or similar) - Experience working with APIs and database integrations - Proficiency in SQL and scripting languages (Python or similar) - Familiarity with distributed data processing frameworks Nice to Have - Experience with AWS data services - Knowledge of infrastructure as code tools - Familiarity with data lake architectures - Experience with Spark or similar technologies - Experience with data pipeline orchestration tools Soft Skills - Analytical thinking - Problem-solving skills - Collaborative mindset - Attention to detail

Lead Data Architect Location: Remote, US based Position type: Full Time Employee Compensation: $190.000 (base + bonus) Job Summary Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and beyond. Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management. We have a diverse, global team of consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture. As part of our growth and upcoming initiatives, we are proactively searching for Lead Data Architects to support future data platform modernization initiatives across our client portfolio. Position Summary The Lead Data Architect will lead the architecture assessment, transition planning, and modernization of the client’s data platform. This role will be responsible for designing the future-state architecture, defining best practices for ELT pipelines, and guiding the migration of existing SQL-based transformations into a scalable dbt framework within a Snowflake environment. The position will work closely with the client’s engineering teams and internal Data Meaning consultants, leading knowledge transfer sessions, architecture walkthroughs, and platform transition initiatives to ensure long-term scalability, reliability, and governance of the data platform. Key Responsibilities: - Lead architecture assessment and documentation of the current data platform (Snowflake, Airflow, AWS) - Design the future-state data platform architecture following modern ELT and dbt best practices - Define standards for: data modeling, pipeline architecture, transformation frameworks, governance and data quality - Lead the migration of transformation logic into dbt models - Define architectural patterns for: staging layers, intermediate layers, data marts - Implement automated testing frameworks within dbt - Lead discovery sessions and technical workshops with the client’s data engineering teams - Document architecture, pipelines, and operational processes - Conduct architecture walkthrough sessions during knowledge transfer phases - Define standards for CI/CD, monitoring frameworks, and data quality validation - Establish schema management and governance best practices - Optimize Snowflake compute usage and platform performance - Design scalable orchestration strategies for Airflow pipelines - Improve platform reliability, monitoring, and operational observability Required Skills & Qualifications: - Advanced / fluent English - 10+ years of experience in Data Engineering or Data Architecture - Strong experience designing and implementing modern data platforms - Expert-level experience with Snowflake - Strong experience implementing dbt transformation frameworks - Advanced SQL modeling and performance optimization - Strong experience with Apache Airflow orchestration - Strong Python programming skills - Experience designing: ELT pipelines, Data warehouse architectures, Transformation frameworks, Large-scale data pipelines - Experience working in cloud environments (AWS preferred) Nice to Have - Snowflake certification - Experience leading data platform migrations or modernization initiatives - Experience implementing Medallion architecture patterns - Experience defining data governance frameworks - Experience working with distributed or global engineering teams

Role Description The Consulting Data Engineer role requires experience in both traditional warehousing technologies (e.g. Teradata, Oracle, SQL Server) and modern database/data warehouse technologies (e.g., AWS Redshift, Azure Synapse, Google Big Query, Snowflake), as well as expertise in ETL tools and frameworks (e.g. SSIS, Azure Data Factory, AWS Glue, Matillion, Talend), with a focus on how these technologies affect business outcomes. This person should have experience with both on-premise and cloud deployments of these technologies and in transforming data to adhere to logical and physical data models, data architectures, and engineering a dataflow to meet business needs. This role will support engagements such as data lake design, data management, migrations of data warehouses to the cloud, and database security models, and ideally should have experience in a large enterprise in these areas. Qualifications - Bachelor’s Degree in Arts/Sciences (BA/BS) or related field - A combination of education, training and experience may be considered in lieu of a degree - A minimum of 3-5 years progressive experience in a related field - Experience with at least one traditional data warehousing technology (e.g., Teradata, Oracle, SQL Server) and/or modern platforms (e.g., AWS, GCP, Azure) - Experience in one scripting language (e.g. Python, Java, Scala) - Experience in SQL scripting, tuning, indexing, partitioning, data access patterns, and scaling strategies - Experience with data integrations and data processing for business intelligence and analytics workloads - Experience as a key player in developing an enterprise data warehouse - US Security Clearance is Required - currently have security clearance Requirements - Ability to translate a logical data model into a relational or non-relational solution - Expert in one or more of the following ETL tools: SSIS, Azure Data Factory, AWS Glue, Matillion, Talend, Informatica, Fivetran - Hands-on experience in setting up End to End cloud-based data lakes - Hands-on experience in database development using views, SQL scripts and transformations - Ability to translate complex business problems into data-driven solutions - Working knowledge of reporting tools like Power BI, Tableau, etc. - Ability to identify data quality issues that could affect business outcomes - Flexibility in working across different database technologies and propensity to learn new platforms on-the-fly - Strong interpersonal skills - Team player prepared to lead or support depending on situation - Travel Requirements: Up to 25% of the time Domestic and International Travel Benefits - Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program - Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement - Paid Time Off: PTO and Sick Leave (starting at 20 days per year) & Holidays (10 per year), Parental Leave, Military Leave, Bereavement - Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program

Data Platform Engineer This is a vacancy for the 26-27 school year with a target start date of July 1, 2026 Mission: The Data Platform Engineer builds and operates IDEA’s data infrastructure on Snowflake, enabling reliable, scalable access to data that supports analytics, reporting, and research across multiple states. This role designs automated ingestion pipelines, optimizes platform performance and cost, and ensures the data platform functions as a production-grade system for downstream teams. Reporting to the Manager of Data Platform Engineering, this engineer works hands-on with ELT pipelines, infrastructure-as-code, and Snowflake administration while contributing to IDEA’s transition from legacy ETL systems to a modern lakehouse architecture. Supervisory Responsibilities: Individual contributor role with no direct reports. Senior engineers may mentor peers and lead technical initiatives. Location: This is a full-time remote position based in Texas, with preference given to candidates who live in Austin, El Paso, Houston, Permian Basin (Midland/Odessa), Rio Grande Valley, San Antonio, and Tarrant County (Fort Worth), or who are willing to relocate. Travel Expectations: Minimal travel (5–10% annually) for collaboration, training, or critical implementation milestones. What You’ll Do – Accountabilities Essential Duties: - Design, build, and maintain automated ELT pipelines ingesting data from diverse source systems into Snowflake. - Configure and manage cloud-native ingestion tools and custom Python-based pipelines when needed. - Build and maintain Bronze-layer tables with schema evolution handling, audit metadata, and lineage. - Implement ingestion-level validation and monitoring to catch issues early. - Document source configurations, refresh schedules, and troubleshooting procedures. - Partner with Analytics Engineering to ensure ingestion patterns support downstream transformation needs. - Administer Snowflake environments, including databases, schemas, warehouses, access controls, and security settings. Additional Duties and Responsibilities: - Optimize performance and cost through warehouse sizing, clustering, query analysis, and resource monitoring. - Manage Snowflake objects using infrastructure-as-code patterns. - Implement security best practices including RBAC, encryption, auditing, and network policies. - Evaluate and adopt new Snowflake capabilities as appropriate. - Own Terraform-based infrastructure definitions for Snowflake and related platform components. - Automate recurring operational tasks such as provisioning, access grants, and environment setup. - Build CI/CD pipelines for infrastructure changes with testing and safe deployment practices. - Develop reusable templates and modules to accelerate onboarding of new sources and domains. - Maintain clear documentation and runbooks for platform operations. - Implement monitoring and alerting for pipelines, platform health, and performance. - Troubleshoot pipeline failures and platform issues using systematic root-cause analysis. - Embed observability (logging, metrics, alerts) into all production pipelines. - Collaborate closely with Analytics Engineering, DataOps, and Data Governance partners. - Participate in code reviews and design discussions. - Share platform knowledge through documentation, mentoring, and team forums. - Contribute to retrospectives and continuous improvement efforts. Knowledge and Skills – Competencies - Make Strategic Decisions: This team member uses data, feedback, and insights to inform thoughtful decision-making, while considering the impact on their direct reports and team. They communicate decisions with clear rationale and begin to connect their choices to broader team objectives. - Manage Work and Teams: This team member sets clear, measurable goals and regularly reflects on progress, adjusting actions as needed. They prioritize work aligned with their goals using a task management system and consistently meet deadlines through effective time management. - Grow Self and Others: This team member regularly offers affirming and adjusting feedback, maintaining a positive balance that reinforces growth and motivation. They provide transparent, candid performance insights and offer consistent coaching and development aligned with individual goals, supporting both direct reports and cross-functional partners. - Build a Culture of Trust: This team member proactively builds strong personal and professional relationships with individual stakeholders and regularly seeks feedback to improve their work experience. They create a supportive environment where others feel safe to take risks and learn from mistakes without fear of retribution. - Communicate Deliberately: This team member communicates thoughtfully by anticipating potential misunderstandings and providing necessary context to ensure clarity. They leverage structured communication channels to address challenges, ask meaningful questions, and guide conversations toward solutions, while actively listening to the concerns of others. Additional Skills: Required - Hands-on experience administering Snowflake or similar cloud data platforms. - Strong SQL skills for data extraction, validation, and performance tuning. - Experience building and operating automated data pipelines. - Proficiency with Python and scripting for automation and operational tooling. - Experience operating production systems with monitoring and incident response. - Familiarity with infrastructure-as-code and CI/CD concepts. Preferred - Experience with cloud-native ingestion tools (e.g., Fivetran, Airbyte). - Experience with Terraform or similar IaC tooling. - Familiarity with dbt and analytics engineering workflows. - Exposure to orchestration, data quality, or observability tools. - Experience with education, public sector, or regulated data environments. Required Education and Experience: - Bachelor’s degree in a technical field or equivalent practical experience. - 3+ years of experience in data engineering, platform engineering, or related roles. - Demonstrated experience building and operating production data systems. - Hands-on experience with Snowflake or comparable cloud data warehouses. Preferred Education and Experience: - Snowflake or cloud platform certifications. - Experience supporting multi-team data platforms at scale. - Strong Python proficiency beyond basic scripting. Physical Requirements: - Prolonged periods working on a computer and in virtual meetings - Ability to travel domestically via car and air travel to campuses and state office - Flexibility for occasional evening meetings with distributed stakeholders across time zones What We Offer: Compensation & Benefits: Salaries for people entering this role typically fall between $89,600 and $105,300, commensurate with relevant experience and qualifications and in alignment with internal equity. This role is also eligible for performance pay based on organizational performance and goal attainment. Additionally, we offer medical, dental, and vision plans, disability, life insurance, parenting benefits, flexible spending account options, generous vacation time, referral bonuses, professional development, and a 403(b) plan. You can find more information about our benefits at https://ideapublicschools.org/careers/benefits/. * IDEA may offer a relocation stipend to defray the cost of moving for this role, if applicable. Application process: Submit your application online through Jobvite. Please note that applications will be reviewed on an ongoing basis until the position is filled. Applicants are encouraged to apply as early as possible. Learn more about IDEA At IDEA the Staff Experience Team uses our Core Values to promote human connection and a culture of integrity, respect, and belonging for all Team and Family members. Learn more about our Commitment to Core Values here: https://ideapublicschools.org/our-story/#core-values