Job Summary
TAIT is seeking a hands-on Data Platform Engineer to help build and scale our enterprise data platform as part of a significant technology transformation. Reporting to the Data Architect, this role will design, develop, and operate modern data solutions using Databricks, AWS, Python, PySpark, SQL, and Lakehouse architectures.
The successful candidate will create trusted data products, scalable pipelines, and analytics-ready datasets that support business-critical reporting, forecasting, operational optimization, and AI/ML initiatives across Finance, Sales, Operations, Manufacturing, Project Delivery, and other enterprise functions.
This role is ideal for an experienced engineer who enjoys building production-grade cloud data platforms, partnering with business and technology teams, and turning complex enterprise data into actionable insights.
Key Responsibilities
Data Platform Engineering
- Design, build, and support enterprise data pipelines and lakehouse solutions using Databricks on AWS.
- Develop scalable ingestion, transformation, orchestration, and data-serving capabilities for batch, streaming, API, file-based, and CDC workloads.
- Build secure, reliable, and cost-effective data platform services leveraging AWS technologies including S3, IAM, KMS, VPC, CloudWatch, and Secrets Manager.
- Implement CI/CD, infrastructure-as-code, automated testing, monitoring, observability, and operational support practices.
Data Products & Analytics
- Create trusted data products, curated datasets, and data models that support Power BI, advanced analytics, forecasting, and AI initiatives.
- Integrate enterprise data across systems including Salesforce, ERP, PSA, MES, PLM, HCM, and other business platforms.
- Support KPI reporting, profitability analysis, resource planning, forecasting, optimization, and executive decision-making.
- Develop reusable, AI-ready datasets that accelerate analytics and machine learning initiatives.
Enterprise Transformation & Governance
- Support cloud transformation, ERP modernization, M&A integration, and enterprise data initiatives.
- Implement data quality controls, governance practices, lineage, cataloging, security, and access management.
- Establish trusted sources of truth and promote standardized, governed data across the organization.
- Partner with architecture, integration, infrastructure, security, and business teams to deliver scalable data solutions.
Collaboration & Delivery
- Lead engineering efforts from solution design through production deployment and ongoing support.
- Communicate technical recommendations and tradeoffs to technical and business stakeholders.
- Participate in architecture reviews, code reviews, roadmap planning, and continuous improvement initiatives.
- Mentor team members and help establish best practices across the data engineering function.
Required Qualifications:
- Bachelor's degree in computer science, engineering, information systems, data science, or a related discipline, or equivalent practical experience.
- 7+ years of professional experience in data engineering, analytics engineering, data platform engineering, or a closely related role.
- A proven track record designing, delivering, and operating production-grade solutions in Databricks on AWS, including responsibility for architecture implementation, pipeline development, deployment, support, performance, and cost.
- Evidence of delivering multiple end-to-end projects where engineered data products enabled sophisticated analysis - such as cross-system KPI reporting, forecasting, optimization, profitability analysis, anomaly detection, predictive modeling, scenario analysis, or AI/ML - with clear business outcomes.
- Advanced SQL and strong Python/PySpark skills, including experience developing maintainable, tested, production-quality code for large and complex datasets.
- Strong knowledge of Spark, Delta Lake or comparable lakehouse patterns, dimensional and analytical data modeling, partitioning, schema evolution, data contracts, and performance tuning.
- Hands-on experience with core AWS data-platform capabilities such as S3, IAM, KMS, VPC networking, CloudWatch, Secrets Manager, and related services used to secure, integrate, and operate Databricks workloads.
- Experience building batch and incremental pipelines using APIs, files, databases, SaaS connectors, change data capture, and at least one orchestration framework or managed workflow capability.
- Experience with Git-based development, CI/CD, automated data testing, code review, environment management, and infrastructure-as-code practices.
- Practical experience implementing data quality, observability, cataloging, lineage, access control, and operational support for business-critical data products.
- Strong problem-solving, documentation, and communication skills, including the ability to translate ambiguous business needs into pragmatic technical solutions and explain data issues in business terms.
- Ability to work independently in a changing environment, prioritize based on business value and risk, and collaborate effectively across architecture, integration, infrastructure, security, applications, analytics, and business teams.
Preferred Qualifications:
- Databricks certification and/or AWS certification relevant to data engineering, analytics, or cloud architecture.
- Experience with Unity Catalog or comparable governance capabilities, including fine-grained access, lineage, cataloging, and multi-environment administration.
- Experience preparing governed data models for Power BI, including semantic-model design, incremental refresh patterns, performance optimization, and row-level security.
- Experience integrating enterprise applications such as Salesforce, Epicor or another ERP, Kantata or another PSA, CPQ, MES, PLM, HCM, EPM, and service management platforms.
- Experience with MuleSoft or another enterprise integration platform and with designing API- or event-driven data exchange patterns.
- Experience enabling machine learning or AI solutions through feature engineering, model-ready datasets, ML lifecycle tooling, vector or unstructured-data pipelines, or responsible AI data controls.
- Experience in a global, project-based, manufacturing, engineering, live-entertainment, or operationally complex business environment.
- Experience supporting enterprise transformation, ERP replacement, legacy-platform retirement, cloud migration, and/or M&A integration.
Pay: $130,000.00 - $140,000.00 per year
Benefits:
- 401(k) matching
- Dental insurance
- Employee assistance program
- Health savings account
- Life insurance
- Paid time off
- Parental leave
- Vision insurance
Work Location: In person
