Note: The job is a remote job and is open to candidates in USA. EazyML specializes in Responsible AI solutions that support enterprise AI compliance and sustainable automation. The Tech Lead will lead the design, development, and delivery of scalable Databricks-based data engineering and AI/ML solutions while guiding engineers and contributing hands-on to architecture, coding, and problem-solving.
Responsibilities
- Lead the technical design and architecture of large-scale data engineering and AI/ML solutions on Databricks (Lakehouse Platform)
- Provide hands-on technical leadership across the full data lifecycle: ingestion, transformation, storage, and consumption using Spark, Delta Lake, and Databricks workflows
- Design and implement scalable ETL/ELT pipelines, ensuring performance, reliability, and cost optimization
- Guide the team in building and deploying AI/ML models and GenAI/LLM-based solutions, integrating them into production data pipelines
- Collaborate with data scientists, ML engineers, and business stakeholders to translate requirements into robust technical solutions
- Establish and enforce best practices for data governance, security, CI/CD, and DataOps/MLOps within Databricks environments
- Mentor and coach a team of data engineers, conducting code reviews and driving engineering excellence
- Own technical decision-making, including platform architecture, tool selection, and performance tuning
- Act as the primary technical point of contact for client/stakeholder discussions, ensuring alignment between business goals and technical execution
- Stay current with evolving Databricks features, Delta Lake updates, and AI/GenAI trends, driving adoption of relevant innovations
Skills
- • 8+ years of overall experience in data engineering, with 3+ years in a technical leadership or lead role
- • Strong hands-on experience with Databricks , including:
- • Spark (PySpark/Scala), Delta Lake, Unity Catalog
- • Databricks Workflows/Jobs, Cluster management & optimization
- • Databricks SQL and performance tuning
- • Solid experience in Data Engineering , including:
- • Building and optimizing ETL/ELT pipelines at scale
- • Data modeling (batch and streaming)
- • Working with cloud data platforms (Azure/AWS/GCP – specify as needed)
- • Experience with orchestration tools (e.g., Airflow, ADF, Databricks Workflows)
- • Practical experience in AI/ML , including:
- • Building, training, and deploying ML models
- • MLOps practices for model lifecycle management
- • Strong programming skills in Python and SQL ; familiarity with Scala is a plus
- • Experience with CI/CD pipelines and version control (Git-based workflows)
- • Solid understanding of data security, governance, and compliance best practices
- • Excellent communication and stakeholder management skills, with the ability to work directly with onshore clients/business teams
- • Proven experience leading and mentoring technical teams
- • Strong ownership mindset with the ability to balance hands-on delivery and team leadership
- • Excellent problem-solving and analytical thinking
- • Strong communication skills to bridge technical and business conversations
- • Ability to work independently in a fast-paced, onshore client-facing environment
- This is a fully remote role with the flexibility to work from anywhere in USA, must have authorization to work in US
- • Familiarity with GenAI/LLM frameworks (e.g., LangChain, RAG pipelines, vector databases) is a strong plus
- • Databricks certification(s) (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Machine Learning Professional)
- • Cloud certification (Azure/AWS/GCP)
- • Experience in Agile/Scrum delivery environments
- • Prior experience working in client-facing consulting or professional services roles
Benefits
- Fully remote role with the flexibility to work from anywhere in USA
- Opportunity to work on cutting-edge agentic AI systems
- Work alongside a team connected to leading AI ventures like Amelia.ai
Company Overview