Capgemini

Databricks Lead

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SeniorHybryda·WarszawaFull-time

#463350·Dodano 24 dni temu·0

Źródło: Capgemini

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Tech Stack / Keywords

Databricks SparkDelta LakeUnity CatalogLakeflowDatabricks SQLMLflow Terraform AzureMosaic AI

Podsumowanie oferty

Lead the Databricks team’s architecture, delivery and people across client engagements. Own lakehouse design and delivery, including data engineering, analytics, machine learning and generative AI using Databricks, Azure, AWS and GCP.

Wymagania

8+ years in data engineering or data architecture, including at least 4 years on Databricks and several years leading engineers or delivery teams.
Proven end-to-end delivery of at least two production lakehouse platforms, covering platform setup, ingestion and pipelines, data models, analytics or ML consumption, and operations.
Deep hands-on knowledge of Spark, Delta Lake, Unity Catalog, Lakeflow pipelines and jobs (formerly Delta Live Tables and Workflows), Databricks SQL and MLflow; infrastructure as code using Terraform and Databricks Asset Bundles; and CI/CD.
Strong experience with one cloud (preferably Azure) and ability to work with AWS or GCP, including networking, identity, storage, security and cost.
Experience tuning performance and optimising costs for Databricks workloads.
Databricks Certified Data Engineer Professional certification.
Presales experience in solution design, estimation and client presentations, including defending architecture and its cost to executives.
Experience leading and developing engineers; excellent communication skills; fluent English.

Nice to have:

Experience with analytics and ML workloads, including Databricks SQL, AI/BI and Mosaic AI.
Further Databricks certifications or partner accreditations, such as Solutions Architect or Platform Administrator.
Experience in financial services, energy, pharma or the public sector.

Obowiązki

Own lakehouse architecture for client engagements, including account and workspace design, networking and identity, Unity Catalog, data models, compute and cost strategy, and CI/CD.
Lead Databricks programmes end to end, including legacy warehouse and Hadoop migrations, greenfield lakehouse builds, platform hardening and cost reviews; set engineering standards for code review, testing, Databricks Asset Bundles and Terraform.
Deliver data engineering, analytics and ML on the platform, including ingestion with Lakeflow Connect, pipelines and data products, Databricks SQL and AI/BI, machine learning and generative AI with MLflow and Mosaic AI, performance tuning and cost optimisation.
Lead and grow the Databricks engineering team through hiring, technical coaching, certification planning and staffing across engagements.
Run the technical side of bids, including solution design, estimates, proofs of concept, sizing and cost models; present architecture choices and costs to client architects and executives.
Implement governance designs on the platform, including access models in Unity Catalog, lineage and audit evidence, data quality in pipelines, and model governance with MLflow.
Build reusable assets, including reference architectures, migration playbooks, ingestion and cost accelerators, platform standards, and a governance-by-design reference architecture.
Follow the Databricks roadmap, including Lakeflow, Mosaic AI, AI/BI, Lakebase and serverless, and decide what to adopt, when and for which clients.

Benefity

Yearly financial bonus.
Private medical care with Medicover, with additional packages available on preferential terms.
Life insurance.
Access to the NAIS benefit platform.
Access to over 70 training tracks and certification opportunities on the NEXT platform.
Free access to the Education First languages platform, TED Talks and Udemy Business materials and trainings.
Home office package including a laptop, monitor and chair.

Premie

Opieka zdrowotna

Ubezpieczenie

Szkolenia wewnętrzne

Capgemini

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