The Role
Lead enterprise data platform architecture and client implementations centered on Databricks and lakehouse technologies. Design data models, governance, security, scalable pipelines, CI/CD, observability, and cost-management strategies. Develop and optimize batch and streaming workloads using Spark, PySpark, Scala, and SQL across cloud and hybrid databases. Mentor data engineering teams, review architectures and code, resolve complex platform issues, and collaborate with business, security, infrastructure, BI, and ML stakeholders to deliver reliable data products.
Summary Generated by Built In
Allata is a global consulting and technology services firm founded in 2016, with 350+ employees across the US, India, and Argentina. We partner with some of the world's largest enterprises to move AI from idea to production — building intelligent agents, data foundations, and governance frameworks that scale.
Our teams work at the intersection of strategy, engineering, data, and design, helping clients modernize their technology, unlock data value, and create meaningful digital experiences. At Allata, you'll join an agile, cross-functional team that works closely alongside clients — making a real impact and building lasting partnerships.
We are looking for a Databricks Manager with strong experience in enterprise data platform architecture and governance to lead client-facing data platform implementations. This role blends high-impact architectural responsibilities (reference architectures, security, scalability, cost management, operational model) with technical leadership in designing, building, deploying, and optimizing data pipelines and data products on Lakehouse/EDW platforms (with an emphasis on Databricks). You will own the full lifecycle of data products and standardize patterns, tools, and practices across large-scale, vertical-specific implementations for our clients.
Role & Responsibilities:
- Define the overall data platform architecture (Lakehouse/EDW), including reference patterns (Medallion, Lambda, Kappa), technology selection, and integration blueprint.
- Design conceptual, logical, and physical data models to support multi-tenant and vertical-specific data products; standardize logical layers (ingest/raw, staged/curated, serving).
- Establish data governance, metadata, cataloging (e.g., Unity Catalog), lineage, data contracts, and classification practices to support analytics and ML use cases.
- Define security and compliance controls: access management (RBAC/IAM), data masking, encryption (in transit/at rest), network segmentation, and audit policies.
- Architect scalability, high availability, disaster recovery (RPO/RTO), and capacity & cost management strategies for cloud and hybrid deployments.
- Lead selection and integration of platform components (Databricks, Delta Lake, Delta Live Tables, Fivetran, Azure Data Factory / Data Fabric, orchestration, monitoring/observability).
- Design and enforce CI/CD patterns for data artifacts (notebooks, packages, infra-as-code), including testing, automated deployments and rollback strategies.
- Define ingestion patterns (batch & streaming), file compacting/compaction strategies, partitioning schemes, and storage layout to optimize IO and costs.
- Specify observability practices: metrics, SLAs, health dashboards, structured logging, tracing, and alerting for pipelines and jobs.
- Act as technical authority and mentor for Data Engineering teams; perform architecture and code reviews for critical components.
- Collaborate with stakeholders (Data Product Owners, Security, Infrastructure, BI, ML) to translate business requirements into technical solutions and roadmap.
- Design, develop, test, and deploy processing modules using Spark (PySpark/Scala), Spark SQL, and database stored procedures where applicable.
- Build and optimize data pipelines on Databricks and complementary engines (SQL Server, Azure SQL, AWS RDS/Aurora, PostgreSQL, Oracle).
- Implement DevOps practices: infra-as-code, CI/CD pipelines (ingestion, transformation, tests, deployment), automated testing and version control.
- Troubleshoot and resolve complex data quality, performance, and availability issues; recommend and implement continuous improvements.
Hard Skills - Must have:
- Previous experience as architect or lead technical role on enterprise data platforms.
- Hands-on experience with Databricks technologies (Delta Lake, Unity Catalog, Delta Live Tables, Auto Loader, Structured Streaming).
- Strong expertise in Spark (PySpark and/or Scala), Spark SQL and distributed job optimization.
- Solid background in data warehouse and lakehouse design; practical familiarity with Medallion/Lambda/Kappa patterns.
- Experience integrating SaaS/ETL/connectors (e.g., Fivetran), orchestration platforms (Airflow, Azure Data Factory, Data Fabric) and ELT/ETL tooling.
- Experience with relational and hybrid databases: MS SQL Server, PostgreSQL, Oracle, Azure SQL, AWS RDS/Aurora or equivalents.
- Proficiency in CI/CD for data pipelines (Azure DevOps, GitHub Actions, Jenkins, or similar) and packaging/deployment of artifacts (.whl, containers).
- Experience with batch and streaming processing, file compaction, partitioning strategies and storage tuning.
- Good understanding of cloud security, IAM/RBAC, encryption, VPC/VNet concepts, and cloud networking.
- Familiarity with observability and monitoring tools (Prometheus, Grafana, Datadog, native cloud monitoring, or equivalent).
Hard Skills - Nice to have/It's a plus:
- Automation experience with CICD pipelines to support deployment and integration workflows including trunk-based development using automation services such as Azure DevOps, Jenkins, Octopus.
- Advanced proficiency in Pyspark for advanced data processing tasks.
- Advance proficiency in spark workflow optimization and orchestration using tools such as Asset Bundles or DAG (Directed Acyclic Graph) orchestration.
- Certifications: Databricks Certified Data Engineer / Databricks Certified Professional Architect, cloud architect/data certifications (AWS/Azure/GCP).
Soft Skills / Business Specific Skills:
- Ability to identify, troubleshoot, and resolve complex data issues effectively.
- Strong teamwork, communication skills and intellectual curiosity to work collaboratively and effectively with cross-functional teams.
- Commitment to delivering high-quality, accurate, and reliable data products solutions.
- Willingness to embrace new tools, technologies, and methodologies.
- Innovative thinker with a proactive approach to overcoming challenges.
At Allata, we value differences.
Allata is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Allata makes employment decisions without regard to race, color, creed, religion, age, ancestry, national origin, veteran status, sex, sexual orientation, gender, gender identity, gender expression, marital status, disability or any other legally protected category.
This policy applies to all terms and conditions of employment, including but not limited to, recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
Skills Required
- Previous experience as an architect or in a lead technical role on enterprise data platforms
- Hands-on experience with Databricks, Delta Lake, Unity Catalog, Delta Live Tables, Auto Loader, and Structured Streaming
- Strong expertise in Spark, including PySpark and/or Scala, Spark SQL, and distributed job optimization
- Experience designing data warehouses and lakehouses using Medallion, Lambda, or Kappa patterns
- Experience integrating SaaS, ETL, ELT, connectors, and orchestration platforms such as Fivetran, Airflow, Azure Data Factory, or Microsoft Fabric
- Experience with relational and hybrid databases including SQL Server, PostgreSQL, Oracle, Azure SQL, AWS RDS, or Amazon Aurora
- Proficiency in CI/CD for data pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools
- Experience packaging and deploying data artifacts such as wheel packages and containers
- Experience with batch and streaming processing, file compaction, partitioning, and storage tuning
- Understanding of cloud security, IAM, RBAC, encryption, VPC/VNet concepts, and cloud networking
- Familiarity with observability and monitoring tools such as Prometheus, Grafana, Datadog, or native cloud monitoring
- Automation experience with CI/CD deployment and integration workflows, including trunk-based development
- Advanced PySpark proficiency
- Advanced Spark workflow optimization and orchestration using Asset Bundles or DAG orchestration
- Databricks Certified Data Engineer or Databricks Certified Professional Architect certification
- Cloud architect or data certifications in AWS, Azure, or GCP
- Strong troubleshooting, communication, teamwork, intellectual curiosity, and cross-functional collaboration skills
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The Company
What We Do
Allata (pronounced a-ley-ta) is a strategy, architecture and enterprise-level application development company focused on helping clients enhance or scale business opportunities, create efficiencies and automate processes through custom technologies. We are building a different kind of firm – focused on doing exciting, transformational work for great clients and bringing caring and dedicated people to make our clients goals a reality. Our vision is to build an energized group of talented professionals that can stand strong on their own but work better as a networked team. We enable business agility at the intersection of people, process, and technology. We provide solutions and expert services to assist businesses to become more nimble, transformative, and disruptive in their respective industries. We define vision, strategy, and value creation models for shaping strategic product designs, managing, and transforming enterprise delivery. Just as strongly as we care about our clients, we feel that it is important to give back to the community and non-profits that we are passionate about. Every month, Allata donates 2% of our net income to a charitable cause our team believes in. We live by our mantra: Family comes first, clients are king, we take great care of our people.
