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Lead Database Developer - AI/ML Focus
Lead Database Developer - AI/ML FocusMichael Baker International • Phoenix, AZ, United States
Lead Database Developer - AI / ML Focus

Lead Database Developer - AI / ML Focus

Michael Baker International • Phoenix, AZ, United States
Hace más de 30 días
Tipo de contrato
  • A tiempo completo
Descripción del trabajo

DESCRIPTION

Michael Baker International is seeking a skilled Lead Database Developer with AI / ML expertise to architect, build, and scale intelligent, data-driven applications across our enterprise ecosystem. As the Lead Database Developer, you will architect, build, and optimize enterprise-grade data platforms that power AI / ML products, analytics, and automation initiatives. You will lead database developers, partner with data scientists, and own the roadmap for scalable data systems that enable real-time insights and model-driven decision-making. This position reports to VP of Data and AI in the CTO Organization at Michael Baker International.

RESPONSIBILITIES

Data Architecture & Leadership

  • Lead design of scalable data pipelines, ingestion frameworks, and distributed processing systems.
  • Architect enterprise data lake / lakehouse / warehouse solutions (Databricks, Snowflake, BigQuery, Redshift).
  • Guide data engineers on best practices, code quality, and scalable data engineering patterns.
  • Own end-to-end execution of data engineering initiatives, including estimation, delivery, and performance optimization.

AI / ML Engineering Enablement

  • Build ML-ready data environments, feature stores, and training pipelines.
  • Partner with data scientists to productionize ML models with CI / CD / CT.
  • Implement model monitoring, data quality, feature versioning, and automated retraining.
  • Support real-time and batch feature engineering and inference pipelines.

    • Data Development Excellence

  • Develop scalable ELT / ETL pipelines using Spark, PySpark, SQL, Airflow, DBT, Kafka, Kinesis.
  • Build high-quality data models (dimensional, data vault, lakehouse).
  • Implement observability, lineage, and data quality frameworks across all pipelines.

    • MLOps & Cloud Engineering

  • Architect MLOps pipelines using Docker, Kubernetes, Terraform, MLflow, SageMaker, or Vertex AI.
  • Optimize cloud cost, performance, and reliability for large-scale AI / ML workloads.
  • Drive standards for cloud data infrastructure and reusable data engineering components.

    • Governance, Security & Compliance

  • Ensure compliance with SOC2, GDPR, PII standards based on company needs.
  • Implement secure data-sharing, encryption, IAM, tokenization, and access patterns.
  • Maintain metadata, cataloging, governance processes (Collibra, Alation, Unity Catalog).

    • Innovation & GenAI Readiness

  • Champion emerging technologies including GenAI, vector databases, and LLM-based pipelines.
  • Drive innovation in AI / ML data engineering and real-time analytics.

    • Team Development and Stakeholder Engagement

  • Lead and mentor data engineering teams.
  • Collaborate with data scientists, ML engineers, and business stakeholders to deliver impactful solutions.
  • Translate business requirements into scalable data strategies.

    • PROFESSIONAL REQUIREMENTS

  • Bachelor’s degree in Computer Science or related field, or similar, or equivalent experience.
  • Any Data or AI / ML related certifications.
  • 6–12+ years of data engineering experience with 2–5+ years in a lead role.
  • Strong programming in Python, SQL; deep expertise in Spark / Databricks.
  • Experience building ML-ready architectures, feature stores, and MLOps pipelines.
  • Expertise with cloud platforms (AWS, Azure, or GCP).
  • Proven ability to lead engineering teams, mentor junior engineers, and drive architectural decisions.

    • PREFERRED QUALIFICATIONS

  • Experience implementing vector databases (Pinecone, FAISS, Milvus) and LLM-based pipelines including RAG.
  • Background in real-time analytics and low-latency ML inference.
  • Experience in highly regulated industries (healthcare, fintech, retail, AEC, manufacturing).
  • Ensure quality, compliance, and security across all data platforms while implementing observability, lineage, and governance frameworks.
  • Define and execute enterprise data strategies aligned with AI / ML initiatives while championing best practices in data engineering, MLOps, and cloud optimization.

    • COMPENSATION

    The approximate compensation range for this position is $130,000 to $170,000. This compensation range is a good-faith estimate for the position at the time of posting. Actual compensation is dependent upon factors such as education, qualifications, experience, skillset, and physical work location.

    BENEFITS​

    We offer a comprehensive benefits package including : ​

  • Medical, dental, vision insurance ​
  • 401 (k) Retirement Plan ​
  • Health Savings Account (HSA) ​
  • Flexible Spending Account (FSA) ​
  • Life, AD&D, short-term, and long-term disability ​
  • Professional and personal development ​
  • Generous paid time off​
  • Commuter and wellness benefits

    • #LI-KR2 #LI-HYBRID

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