Tecsys Inc.

Full-stack Engineer

• Design, build, and maintain scalable ETL/ELT pipelines that ingest and transform structured, semi-structured, and unstructured data
• Develop high-fidelity data pipelines on Databricks/Spark optimized for reliability, cost, performance, and data freshness
• Build curated datasets, embeddings-ready data, feature layers, and semantic abstractions that are AI/ML-consumable for downstream systems
• Implement ingestion, transformation, and serving layers across Data Lake / Lakehouse architectures with a focus on efficient retrieval and contextual usability
• Develop and maintain robust data models including fact/dimension models, SCDs, wide tables, and CDC pipelines
• Apply data versioning, incremental processing, partitioning, and clustering strategies to ensure consistency, reproducibility, and cost efficiency
• Contribute to architectural decisions and trade-offs across storage, compute, and orchestration layers within the analytics platform
• Help define and uphold data modeling standards, data contracts, and quality frameworks across teams
• Prepare high-quality datasets for ML model consumption, feature engineering workflows, and predictive/forecasting use cases
• Contribute to a unified semantic layer that standardizes metrics, reusable definitions, and improves data access patterns
• Partner with Data Science teams to operationalize feature pipelines and support model training, serving, and monitoring
• Implement data quality checks, contracts, and observability to ensure SLA/SLO adherence across pipelines
• Work with metadata, lineage, and data discovery frameworks to improve transparency, governance, and trust in data
• Drive improvements in pipeline reliability, monitoring, and incident response across the data ecosystem
• Partner cross-functionally with Product, Analytics, and Data Science to translate ambiguous business problems into reusable data assets
• Mentor junior engineers, review code/designs, and raise the bar for engineering quality and best practices
• Communicate technical decisions, trade-offs, and system designs clearly to both technical and non-technical stakeholders

Senior Software Developer

DevOps Engineer

• Improve the various deployment and integration tools using containers (Docker)
• Participate in the design and maintenance of CI/CD pipelines
• Employ test-driven development (TDD) techniques
• Develop test automation strategies
• Perform code reviews on the work of your peers
• Participate in team scrum meetings: planning, analysis and retrospectives
• Collaborate with the team to improve continuous integration techniques and processes

Intern – DevOps

QA Engineer

• Design and develop automated tests for Databricks data pipelines and transformations.
• Validate end-to-end data movement across Bronze, Silver, and Gold data layers.
• Create SQL and Python-based validation scripts to verify data quality and business rules.
• Build and maintain automated regression test suites for data pipelines.
• Integrate automated testing into CI/CD pipelines.
• Implement data observability checks, including schema validation, data freshness, volume monitoring, and anomaly detection.
• Investigate data quality issues, perform root cause analysis, and support production releases.
• Collaborate with Data Platform Developers, Product Owners, and business stakeholders in an Agile environment to ensure high-quality data products.

Data Platform QA Engineer, Data Quality, Observability

Pharmacist

• Serve as a Tecsys subject matter expert on pharmacy operations, purchasing workflows, inventory management, regulatory requirements, and industry trends.
• Maintain deep knowledge of pharmacy market dynamics, operational challenges, and evolving customer needs.
• Provide expert guidance on pharmacy regulations and standards, including DSCSA, 340B, controlled substances, medication traceability, and audit requirements.
• Partner with Product Management to translate pharmacy workflows and market needs into scalable software capabilities.
• Help define best-practice product behavior for pharmacy-specific workflows, including:
• pharmacy purchasing and sourcing strategies
• medication procurement and wholesaler ordering
• contract compliance and purchasing optimization
• inventory optimization
• replenishment
• shortage mitigation and substitutions
• lot and expiry management
• pharmacy automation integrations.
• Validate solution designs to ensure they align with real-world pharmacy operations.
• Support Engineering by providing requirements and clarification for complex pharmacy-related initiatives.
• Support strategic sales opportunities by helping validate prospect requirements and demonstrating pharmacy domain credibility.
• Participate in customer discovery sessions, executive discussions, and strategic account engagements.
• Help position Tecsys solutions against market needs and competitive alternatives.
• Advise implementation and services teams on workflow design, best practices, and operational optimization.
• Help identify opportunities to reduce unnecessary customization by promoting scalable best-practice workflows.
• Assist with complex customer challenges and strategic escalations.
• Monitor emerging trends in pharmacy technology, automation, analytics, and AI.
• Help identify strategic opportunities for product investment, partnerships, and innovation.
• Provide pharmacy domain insight to support long-term product strategy and market positioning.

Director, Industry Solutions – Pharmacy

Technical Product Manager

• Own and prioritize the backlog for platform automation, deployment, compliance, and scalability.
• Translate business, security, and regulatory needs into clear epics, user stories, and acceptance criteria.
• Experience using AI tools to accelerate product workflows (requirements drafting, analysis, documentation, backlog refinement), including running structured, spec-driven flows that bring AI assistance into collaborative SDLC practices across engineering, QA, and product.
• Partner with engineering teams to:
• - Automate build, packaging, and deployment workflows
• - Reduce deployment cycle time and increase release confidence through CI/CD improvements
• - Introduce orchestration best practices for zero-downtime deployments
• - Remove manual processes and increase end-to-end automation
• Ensure smooth upgrades across customer environments through deployment playbooks, chart versioning, and environment-specific sequencing.
• Own the product lifecycle for third-party platform components (BI tooling, integration engines, etc.), including containerization, version upgrades, and configuration management.
• Align deployment and automation initiatives with business goals while meeting compliance and certification requirements (FedRAMP, SOC2).
• Track KPIs such as deployment speed, reliability, adoption, and developer experience.
• Support architecture and security teams with design validation and risk assessments.
• Document requirements, decisions, and solution overviews clearly.
• Facilitate cross-team discussions to align scope, dependencies, and timelines.

Technical Product Owner, Platform Delivery

Data Engineer

• Define and execute the product strategy and roadmap across data and AI platform domains
• Own data platform capabilities including ingestion, streaming, transformation, integration, and analytics
• Lead product direction for data quality, governance, security, observability, and scalability
• Partner with engineering, architecture, and cross-functional teams to translate business needs into technical solutions
• Own the vision and delivery of a customer-facing AI platform, including assistants, workflows, and intelligent tools
• Translate customer needs into intuitive, scalable, and impactful AI-driven product experiences
• Drive adoption of AI capabilities by gathering feedback, measuring usage, and iterating based on outcomes
• Manage and prioritize product backlogs, write user stories, and support Agile delivery processes
• Conduct market research and competitive analysis to inform product direction
• Define success metrics and KPIs to guide decision-making and measure impact
• Contribute to go-to-market planning and communicate product vision to stakeholders
• Balance short-term delivery goals with long-term strategic platform investments

Senior Software Developer

Intern – DevOps

Data Platform QA Engineer, Data Quality, Observability

Director, Industry Solutions – Pharmacy

Technical Product Owner, Platform Delivery

Product Manager, Data Platform – AI Platform