Your current job search

• Architect and implement data science deployment solutions tailored to enterprise client needs, focusing on model inference, monitoring, retraining, and infrastructure setup.
• Collaborate with data scientists to prepare and transform data into production-ready formats.
• Build environments for model development and testing, ensuring operational readiness and maintainability.
• Design integration strategies with existing business systems to ensure scalability and long-term success.
• Lead efforts in model QA, testing, validation, and production rollout.
• Champion best practices for software development, model deployment, and infrastructure.

• 6+ years of experience in roles such as ML Engineer, Software Engineer, or Data Engineer. However some kind of background in data engineering is crucial for the role
• Strong background in Python, Scala, Java, or comparable languages.
• Proficient in deploying models in real-world production environments.
• Expertise in SQL and distributed computing tools (e.g., Spark, Snowflake, Databricks).
• Familiarity with various data sources and systems (Kafka, RDBMS, cloud platforms).
• Solid grasp of cloud infrastructure and architecture (e.g., AWS, Azure, GCP).
• Experience in developing APIs or backend applications using modern frameworks.

• Advanced degree in a relevant technical field.
• Hands-on experience with ML tools and frameworks such as TensorFlow, Keras, scikit-learn, or H2O.
• Experience with containerization tools like Docker or Kubernetes.
• Familiarity with model management tools (MLflow, Sagemaker, Azure ML).
• Contributions to open-source projects or relevant personal initiatives.

• Flexible, remote-first working model.
• Culture that values creativity, autonomy, and team collaboration.
• Competitive compensation, strong benefits, and generous PTO.
• Ongoing professional development including certification opportunities.
• Inclusive environment where diverse perspectives are welcomed and celebrated.

• Strong hands-on experience developing data pipelines using Python
• Strong SQL skills, including performance tuning, stored procedures, and data modeling (Star/Snowflake schemas)
• Proven experience with Azure Data Factory (ADF) and Azure Synapse
• Experience with ETL orchestration tools such as Apache Airflow
• Skilled in working with structured and unstructured data, including ingestion from APIs (REST/JSON/XML)
• Familiarity with cloud-based warehousing tools such as Snowflake, Redshift, or BigQuery
• Comfortable working in Azure and/or hybrid cloud environments (Azure/AWS)
• Experience supporting machine learning or predictive modeling pipelines
• Familiar with containerization and version control: Docker, Git, and Azure DevOps
• Understanding of data serialization formats (Parquet, Avro, JSON)
• Knowledge of data validation, quality checks, and observability tools (Azure Monitor, logging frameworks, etc.)

• 
  
  Own the end-to-end design and rollout of AI solutions that accelerate sales forecasting, quote generation, and marketing content creation.
• 
  
  Map current processes in Microsoft Dynamics 365 Business Central (BC); identify data sources, gaps, and integration points for AI.
• 
  
  Architect and implement Azure-based services (Azure OpenAI Service, Cognitive Services, Azure Machine Learning, Data Factory, Synapse, Functions, Logic Apps) to ingest data, train models, and deploy scalable, secure APIs.
• 
  
  Build and maintain reusable forecasting and CPQ models, prompt libraries, and generative-content templates; establish CI/CD and MLOps pipelines.
• 
  
  Define and enforce AI governance: data quality standards, versioning, telemetry, bias mitigation, security, and Responsible AI compliance.
• 
  
  Lead backlog grooming, sprint planning, and cross-functional collaboration with product, marketing, and IT; serve as the technical lead for adoption of AI across the organization
• 
  
  Track and report performance metrics (latency, accuracy, ROI) and continuously optimize models and workflows.

• 
  
  Successful track record of delivering data analytics / software solutions, with recent lead role(s) in production AI/ML and/or generative-AI deployments.
• 
  
  Deep expertise in Azure AI stack (Azure OpenAI, Cognitive Services, Azure Machine Learning, Data Lake, Synapse, Data Factory) and in designing secure, high-availability cloud architectures.
• 
  
  Hands-on knowledge of Microsoft Dynamics 365 Business Central APIs, AL extensions, and Power Platform (Power Automate, Power Apps, Copilot Studio, Dataverse).
• 
  
  Strong programming background (Python, SQL) and proficiency with Git-based CI/CD, RESTful API design, and serverless/event-driven patterns.
• 
  
  Proven delivery of forecasting, CPQ, or marketing-content AI solutions at enterprise scale; fluency in prompt engineering, retrieval-augmented generation, and vector databases (e.g., Azure Cosmos DB, Elastic).
• 
  
  Experience standing up MLOps frameworks (MLflow, Azure ML pipelines) and monitoring for model drift, data shifts, and cost efficiency.
• 
  
  Solid grasp of data governance, privacy (GDPR/CCPA), security best practices, and Responsible AI principles.
• 
  
  Exceptional stakeholder-management and leadership skills; adept at evangelizing new technology and mentoring engineers in an agile environment.

• Data Analysis & Reporting: Analyse organizational performance and trends, identifying significant patterns, outliers, and factors that impact outcomes.

• Insight Generation: Investigate data to reveal patterns and behaviours that can inform business decisions and improve overall performance.

• Strategic Recommendations: Provide recommendations based on analysis to assist leadership with both strategic and operational decisions via white papers.

• Reporting & Presentations: Prepare and present reports to key internal and external teams via power point, helping guide data-driven decision-making.

• Validation Studies: Conduct studies using external data sources to support the company's overall value proposition.

• Data Strategy Development: Propose and implement strategies to enhance data management, accessibility, and reporting processes.

• Technical Tools Usage: Leverage reporting tools such as MicroStrategy to generate in-depth reports and analyses from the data warehouse.

• Flexible Role: This job description outlines the general responsibilities, but additional tasks may arise as needed.

• Education: Bachelor's degree in Computer Science, Information Technology, or a related field (graduate degree preferred).

• Experience: Experience in data analysis, with a strong background in handling large data sets and proficiency with tools such as SPSS, MS-SQL, PL/SQL, SQL, Access, or Python.

• Experience with data visualisation and reporting tools like Power BI, MicroStrategy, or Tableau is essential.

• Ability to independently manage tasks and offer support to junior team members when needed.

• Strong project management and presentation skills are crucial.

• Demonstrates core values such as attention to detail, initiative, and adaptability.

• Strong problem-solving abilities, with a logical approach to analysing data and providing solutions.

• Excellent communication and interpersonal skills, able to present data clearly and professionally.

• Capacity to handle confidential information, ensuring compliance with policies and regulations.

• Advanced proficiency in Microsoft Office and other related software.

• In-depth experience working with database tools and providing technical recommendations to streamline processes.

• Flexible and adaptable to changing priorities, with the ability to meet deadlines in a fast-paced environment.

• Monitor database performance, optimize queries, and conduct regular performance tuning.
• Install, configure, and upgrade database software and associated tools.
• Conduct database maintenance tasks, including backups, index rebuilds, and statistics updates.
• Set up and manage SQL instances for production and test environments, including availability groups and failover clusters.
• Plan for future database capacity and performance requirements.
• Implement proactive monitoring tools and resolve database-related issues.
• Maintain detailed documentation of database schemas, configurations, and procedures.
• Recommend architectural improvements aligned with Microsoft SQL Server best practices.
• Work closely with cross-functional teams including developers, analysts, and IT infrastructure.
• Enforce database security, access controls, and compliance standards.
• Develop and test disaster recovery and failover strategies.

• Bachelor's degree in a related field preferred, or equivalent post-secondary education.
• Minimum 5 years of experience in database/software management with increasing responsibilities.
• Experience managing complex IT projects and working with BI platforms (e.g., Power BI).
• Relevant certifications such as Microsoft DP-300 are advantageous.
• Strong skills in SQL Server administration (2016+), T-SQL, and database performance tuning.
• Familiarity with BI tools like Power BI and Tableau.
• Experience supporting and developing within data warehouse environments.
• Proficiency in database backup/recovery tools and disaster recovery solutions.
• Working knowledge of Microsoft Azure and Active Directory.
• Understanding of Microsoft licensing practices.
• Scripting experience (PowerShell, T-SQL) for automation tasks.
• Ability to mentor team members and manage competing priorities in a fast-paced environment.

• Multiple-time Partner of the Year with top cloud platforms
• 600+ advanced cloud certifications (AWS, Azure, Snowflake, and more)
• Recognized as a best place to work across multiple regions

• Design end-to-end AI/ML solutions ensuring scalability, robustness, and business alignment
• Lead teams of engineers and data scientists to build sophisticated ML platforms, pipelines, and products
• Articulate the business impact and ROI of machine learning initiatives to diverse audiences
• Mentor team members on emerging best practices and industry standards
• Stay current on evolving AI/ML tools and methodologies to shape future solutions

• Forge strong client relationships to understand their AI/ML vision and translate it into actionable roadmaps
• Present compelling technical strategies that drive client adoption and success
• Identify opportunities for additional client value through expanded AI/ML solutions
• Lead responses to RFIs and RFPs, emphasizing innovative and results-driven approaches

• Extensife experience in AI/ML architecture, software engineering, or data science
• Significant leadership experience in a consulting environment
• Bachelor's degree in Computer Science, Engineering, or related field
• Strong expertise deploying machine learning models in production environments
• Demonstrated success in account growth, solution pre-sales, and proposal development
• Deep knowledge of AI/ML ecosystems (AWS, GCP, Azure, Databricks, Vertex AI, SageMaker)
• Proficient in Python, Scala, Java, or other modern programming languages
• Experience with building scalable data pipelines and API/web server development
• Full software development lifecycle experience

• Master's degree or other advanced qualifications
• Contributions to open-source AI/ML projects
• Familiarity with ML libraries (TensorFlow, Keras, scikit-learn, h2o, etc.)
• Experience with Docker, Kubernetes, MLflow, and Sagemaker/Azure ML

• Remote-first work environment
• Award-winning, collaborative culture emphasizing creativity and autonomy
• Competitive compensation and benefits, including 4 weeks PTO plus holidays
• Ongoing investment in advanced training and professional certifications

Job Title: Senior System and Security Administrator

Responsibilities:

• 
  
  Collaborate with stakeholders to gather and analyze system requirements, translating business needs into technical solutions
• 
  
  Lead architectural design and integration of enterprise systems, with a focus on identity management (SSO/SCIM) and cloud platforms (AWS, Azure)
• 
  
  Ensure integration of DNS, email security (SPF, DKIM, DMARC), and device management tools such as Kandji MDM, Intune MDM, and NinjaOne MD
• 
  
  Provide technical guidance and mentorship to development teams, architects, and engineers
• 
  
  Establish and enforce architectural standards, best practices, and guidelines
• 
  
  Develop and enforce IT security frameworks (e.g., NIST CSF, SOC 2)
• 
  
  Oversee and improve deployment of security tools including SentinelOne, Zscaler, Mimecast, and Datadome
• 
  
  Act as a key stakeholder in DNS management, brand protection, and email deliverability
• 
  
  Lead the change control board for SaaS products and serve as a stakeholder for approvals

Qualifications:

• 
  
  Bachelor's degree in Computer Science, Information Technology, or related field, or equivalent experience
• 
  
  7+ years of progressive experience in IT systems and security administration, with at least 2 years in a senior or lead capacity
• 
  
  Proficient in cloud platforms (AWS and Azure)
• 
  
  Strong experience with enterprise applications such as Microsoft 365, Google Workspace, Slack, and Zendesk
• 
  
  Hands-on experience with identity management, including SSO and SCIM
• 
  
  Expertise in DNS, SPF, DKIM, DMARC, and email security best practices
• 
  
  Familiarity with MDM solutions such as Kandji, Intune, and NinjaOne
• 
  
  Experience managing Zscaler, Cisco Meraki, and Zero Trust principles
• 
  
  Solid understanding of IT security standards (NIST CSF, SOC 2)
• 
  
  Comfortable supporting Kubernetes clusters and Microsoft 365 tenant administration
• 
  
  Strong interpersonal and communication skills, with experience mentoring cross-functional teams

• Deep competence with Node.js for back-end development.
• Production experience deploying and operating AWS Lambda functions and Amazon API Gateway integrations.
• Proficiency with serverless design patterns, event buses, and infrastructure-as-code tools such as AWS SAM, CDK, or Terraform.
• Knowledge of data stores suitable for serverless workloads, especially DynamoDB and PostgreSQL.
• Hands-on work integrating AI or machine-learning services into live applications and a strong interest in advancing those capabilities.
• Ability to optimize performance, security, observability, and cost in a serverless environment.

• Shape raw warehouse data into clean tabular models, write reusable DAX, and publish pixel-perfect reports.
• Commit every change to Git, pass automated Tabular Editor checks, and promote through gated Dev, Test, Prod pipelines
• Enforce a "work-item + approval" rule; nothing reaches production without a green build and your pull-request notes
• Stay plugged into monthly Power BI updates, prototype new features, and brief the team on what's worth adopting
• Partner with the hiring manager and the wider data team during roll-outs - answer questions, tweak visuals, and keep dataflows flowing

• 
  
  Pipeline Engineering: Develop and maintain scalable ETL/ELT workflows to support data needs across analytics, operations, and business functions.
• 
  
  Infrastructure Design: Architect and fine-tune data platforms across cloud and hybrid environments for optimized access and performance.
• 
  
  Cross-Functional Collaboration: Partner with data scientists, analysts, engineers, and product teams to deliver reliable, actionable data solutions.
• 
  
  System Performance: Ensure systems are built with scale in mind, proactively managing performance and growth.
• 
  
  End-to-End Ownership: Manage the full data lifecycle-from ingestion through transformation and delivery-without handoffs or silos.
• 
  
  Data Quality & Compliance: Uphold data integrity, security, and traceability in line with internal and regulatory standards.
• 
  
  Innovative Problem Solving: Navigate evolving challenges with a solution-oriented mindset and flexible approach to tools and technologies.
• 
  
  Team Engagement: Contribute to a small, high-impact team where every voice counts and initiative drives progress.

• 
  
  Education: A bachelor's degree in Computer Science, Engineering, or a related discipline (advanced degrees welcomed).
• 
  
  Professional Experience: Solid background in data engineering across data ingestion, transformation, and storage layers.
• 
  
  Technical Proficiency: Strong command of SQL and experience with at least one core technology (e.g., Python, Scala, Spark, Snowflake, AWS, etc.).
• 
  
  Adaptability: Comfortable working in changing technical landscapes and open to evolving tools and priorities.
• 
  
  Data Architecture Knowledge: Deep understanding of database systems, data modeling practices, and cloud-based infrastructure.
• 
  
  Workflow Tools: Experience with orchestration tools like Airflow, dbt, or comparable systems.
• 
  
  Nice to Have: Familiarity with business intelligence platforms such as Power BI, Tableau, or MicroStrategy.

• 
  
  Proactive and solution-focused, not afraid to take ownership.
• 
  
  Strong analytical and systems thinking skills with a practical mindset.
• 
  
  Clear communicator who can articulate technical ideas to various audiences.
• 
  
  Team player who can also thrive in independent settings.
• 
  
  Detail-oriented, reliable, and invested in the team's and company's success.
• 
  
  Agile and professional under pressure, with a flexible approach to shifting priorities.