data platform architect

Jade Global

<div>Data Platform Architect (Microsoft Fabric)
**Experience: 10+ years overall, with 2&ndash;3 years hands-on experience in Microsoft Fabric (project experience required)
 
**Role Type: Contractor
 
**Location: Pune
## Role Overview
 
We are looking for an experienced Data Platform Architect to design and implement a scalable, end-to-end data platform using **Microsoft Fabric**. The role spans architecture, data engineering, modelling, analytics enablement, and integration with advanced data practices such as Medallion Architecture and AI/ML readiness.
<div>## Key Responsibilities
 
### 1) Architecture &amp; Design
 
<ul><li>Define end-to-end architecture for a unified data platform using Microsoft Fabric.
</li><li>Design scalable, secure, and high-performance solutions.
</li><li>Establish integration strategies across enterprise systems (ERP, CRM, SaaS).
</li><li>Enforce data governance, security, and compliance standards.
</li><li>Implement Medallion Architecture (Bronze, Silver, Gold layers) for structured data transformation and quality.
</li></ul></div><div>### 2) Data Engineering &amp; Integration
 
<ul><li>Build data pipelines using Data Factory and Dataflow Gen2.
</li><li>Develop ETL/ELT processes (incremental and full loads).
</li><li>Integrate and transform data into Lakehouse/Data Warehouse.
</li><li>Architect pipelines supporting both batch and real-time processing.
</li><li>Apply DataOps practices and CI/CD for pipeline automation.
</li></ul></div><div>### 3) Data Modelling
 
<ul><li>Design star and snowflake schemas.
</li><li>Define data standards, naming conventions, and best practices.
</li><li>Ensure data quality, consistency, and integrity.
</li><li>Apply dimensional (Kimball) and Lakehouse modelling techniques.
</li></ul></div><div>### 4) Analytics &amp; Semantic Layer
 
<ul><li>Develop semantic models (Power BI datasets).
</li><li>Optimize models for reporting and analytics.
</li><li>Support basic reporting and visualization needs.
</li><li>Enable self-service BI through well-structured semantic layers.
</li></ul></div><div>### 5) Performance Optimization
 
<ul><li>Tune pipelines, storage, and query performance.
</li><li>Apply partitioning, indexing, and cost optimization strategies.
</li><li>Handle large-scale datasets (billions of records) efficiently.
</li></ul></div><div>### 6) Collaboration &amp; Leadership
 
<ul><li>Translate business requirements into technical solutions.
</li><li>Guide data engineers and BI developers.
</li><li>Align architecture, engineering, and analytics teams.
</li><li>Mentor teams and enforce best practices, coding standards, and design patterns.
</li></ul></div><div>### 7) Advanced Capabilities
 
<ul><li>Establish metadata management, lineage tracking, and cataloging frameworks.
</li><li>Provide architectural guidance for AI/ML integration (feature stores, model pipelines).
</li><li>Ensure compliance with regulatory standards (GDPR, HIPAA, etc.).
</li></ul></div><div>## Required Skills
 
<ul><li>10+ years in data/solution architecture.
</li><li>2&ndash;3 years of hands-on Microsoft Fabric experience (must have delivered Fabric projects).
</li><li>Expertise in Lakehouse, Data Warehouse, Data Factory, Dataflow Gen2.
</li><li>Strong SQL and ETL/ELT development skills.
</li><li>Data modelling expertise (star/snowflake schemas, Data Vault, Medallion).
</li><li>Experience with large-scale data and performance tuning.
</li><li>Knowledge of Power BI (datasets, relationships, basic reporting).
</li><li>Understanding of data governance, security, and quality.
</li><li>Strong knowledge of Spark/PySpark for distributed data processing.
</li><li>Experience with CI/CD and DataOps in data engineering.
</li></ul></div><div>## Good to Have
 
<ul><li>Broader Azure ecosystem (ADF, Synapse, ADLS).
</li><li>Python / Spark / PySpark advanced use cases.
</li><li>ERP/CRM integrations.
</li><li>Power BI performance optimization.
</li><li>Familiarity with open table formats (Delta Lake, Parquet).
</li><li>Awareness of integrating ML workflows with Fabric.
</li></ul></div><div>## Success Criteria
 
<ul><li>Scalable and well-architected Fabric platform.
</li><li>Reliable and efficient data pipelines (batch + real-time).
</li><li>High-quality, structured data models with Medallion layering.
</li><li>Seamless data integration across enterprise systems.
</li><li>AI/ML-ready datasets and workflows.
</li><li>Fast and optimized reporting with self-service BI enablement.</li></ul></div></div>

Data Platform Architect (Microsoft Fabric)

Enpal

<div>Our goal is to have a solar system on every roof, a storage unit in every house, and an electric car in every garage. Enpal makes this possible with an integrated total solution for decentralized energy&mdash;from solar systems and battery storage to wall boxes, smart meters, and heat pumps. At the heart of it all is our AI-powered platform Enpal.One+, which intelligently connects thousands of systems and efficiently optimizes electricity procurement and feed-in on the energy market.
Are you ready for solutions that are more than just a promise and bring real quality of life to thousands of households every day? What you create at Enpal will deliver clean electricity tomorrow and bring about lasting change in how we use energy. 
 
About the Role
The Staff Data Platform Architect is a senior technical leadership role responsible for defining and governing best practices across our data platform and analytics ecosystem. Reporting to the Engineering Manager, Data Platform, this is an individual-contributor role that leads through influence and lateral collaboration rather than direct authority.
You will act as a cross-functional technical authority, working closely with the Data Platform team and domain BI teams to set the standards, guardrails, and architectural direction that enable all data teams to operate at high quality and scale. Your impact is measured not by what you execute day-to-day, but by how effectively you raise the bar across teams through clear standards, sound architecture, and trusted consultation. 
What you'll do: 
 
Data Contract Standards<ul><li>
Define and enforce best practices for the technical definition and implementation of data contracts, including guidance documentation and CI/CD enforcement.</li><li>
Establish best practices for the review and actualization of data contracts with data owners, keeping producers and consumers aligned.</li></ul>
Tooling &amp; Developer Experience<ul><li>
Drive tool selection and evolution for data developers (e.g., dbt, IDEs, AI-assisted tooling), continuously evaluating options and defining usage best practices to keep teams productive and modern.</li></ul>
Data Modeling Standards<ul><li>
Set and maintain the reference data model architecture, defining where and how data should be structured across layers (e.g., ODS/bronze, marts).</li><li>
Establish best practices for model quality, code reusability, and data product certification, including SQL style guides and data testing guidelines.</li></ul>
Advisory &amp; Consulting<ul><li>
Serve as a consulting authority for the design and maintenance of data processing infrastructure (Snowflake, dbt, Airflow, dlt, Azure) and BI infrastructure (Power BI, Tableau).</li><li>
Support BI teams in modeling data products within dbt and Snowflake.</li></ul> 
Scope of Influence 
 
This role does not own day-to-day execution but sets the technical direction, standards, and guardrails for all data teams. The work manifests primarily as:<ul><li>
Guidance and governance documentation</li><li>
Technical enforcement mechanisms (CI/CD, testing frameworks)</li><li>
Cross-team consultation and architectural review</li></ul> 
Scope of Influence What you'll bring
Experience &amp; Background<ul><li>
7&ndash;10 years in data engineering, analytics engineering, or data platform roles, with a track record of working as a strong generalist across the modern data stack.</li><li>
Demonstrated experience setting technical standards or architecture that other engineers adopted and built on.</li><li>
Experience operating in a multi-team or domain-oriented data environment (data mesh, federated ownership, or similar) is a strong plus.</li></ul>
Technical Depth<ul><li>
Deep, hands-on expertise with dbt and a cloud data warehouse (Snowflake strongly preferred), including large or modular project structures.</li><li>
Solid command of data modeling approaches across raw, staging, and serving layers, and the trade-offs between them.</li><li>
Working knowledge of orchestration (Airflow), ingestion (dlt), cloud platform (Azure), and BI tooling (Power BI, Tableau).</li><li>
Familiarity with data contracts, schema governance, and CI/CD enforcement for data pipelines.</li><li>
Awareness of AI-assisted developer tooling and a pragmatic, evidence-based view of where it adds value.</li></ul>
Governance &amp; Standards
<ul><li>Proven ability to translate good practice into durable, adoptable standards: style guides, testing frameworks, certification criteria, review processes.</li><li>
Comfort defining guardrails that scale across teams without becoming bottlenecks.</li></ul>
Lateral Leadership &amp; Communication<ul><li>
Strong written communication; able to produce documentation engineers actually read and follow.</li><li>
Ability to build consensus and drive adoption through influence, not authority, across teams with competing priorities.</li><li>
Skilled at the consulting posture: advising, reviewing, and guiding without taking over.</li></ul>
Are you interested even if you don't meet all the requirements? Apply anyway! We look forward to discovering your potential&mdash;regardless of whether your experience meets every single requirement.
<h3 class="jobSectionHeader">What we offer</h3><ul><li>
Work at Germany's first green unicorn - Play an active role in shaping the solar energy transition.</li><li>
The sun shines all over the world - At Enpal, you'll work with a highly motivated, diverse team of over 65 nationalities.</li><li>
The ideal setup for your focus - We are convinced that excellent results are achieved when the conditions are right. That's why we rely on a hybrid working concept that gives you the freedom to always work in the way that best suits your tasks. Do you need new inspiration on an international level? With Workflex, we offer you the opportunity to relocate abroad for up to 30 days a year, depending on your responsibilities.</li><li>
Grown-up business &amp; startup spirit - In our modern office in Berlin-Friedrichshain, you'll find everything your heart desires, from height-adjustable desks and table tennis to stocked beverage fridges and barista coffee.</li><li>
Your kick-start at Enpal - Onboarding day with a welcome bag, buddy program, and a team that really supports you.</li><li>
Stay up to date &amp; help shape the future - Transparent all-hands meetings, short decision-making processes, and an open feedback culture - without mistakes, there is no progress.</li><li>
The energy transition can only be achieved together - At Enpal, you can expect legendary team spirit and unforgettable team events.</li><li>
Your extra boost - 29 vacation days + one additional day off on Christmas Eve and New Year's Eve, discounted membership at Wellhub, and corporate benefits. Everything you need to help you achieve a good work-life balance.</li></ul>
At Enpal, we are proud of the diversity of our team. No decisions are made on the basis of skin colour, religion or religious belief, ethnic or national origin, nationality, gender identity, sexual orientation, disability or age, either during recruitment or employment. Enpal stands for a safe workplace and takes action against discrimination and harassment of any kind.</div>

Data Platform Architect (f/m/x)

Capgemini

<div><div><div><div><div><div><div><h2 class="jobSectionHeader">Who You'll Be Working With</h2> 
</div><div>As a Data Solution Architect at Capgemini, you will design and lead the delivery of modern data platforms that enable analytics, AI, GenAI, and data driven decision making at scale. You will translate business strategy into robust, governed, and AI ready architectures, taking end to end ownership from vision through to delivery and value realisation. 
 
You will be part of the Data Platforms team that is part of the Insights and Data Global Practice that has seen strong growth and continued success across a variety of projects and sectors. Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms. We specialise on using the latest frameworks, reference architectures and technologies using AWS and GCP along with various data platforms like Databricks and Snowflake 
Please Note: Security Clearance: To be successfully appointed to this role, must be eligible to obtain Security Check (SC)clearance.
 
To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.
Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality.
 
Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.
</div></div><div><div><h2 class="jobSectionHeader">The Focus Of Your Role</h2> 
</div><div>As a Solution Architect with a Databricks focus, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will combine deep Databricks and Apache Spark expertise with strong client engagement skills to shape solutions from early-stage opportunity through delivery. You will lead our Databricks partnership activity, helping develop joint propositions, enablement, and go-to-market plans, and you will support pre-sales by contributing to discovery, solution design, estimates, and compelling client-facing materials. 
<ul><li>Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data across cloud and on-premises sources and targets.</li>
<li>Design and oversee the delivery of secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data.</li>
<li>Ability to design, build and deploy AI/ML models: Integrate Machine Learning into data pipelines and leverage Databricks capabilities to develop predictive models and drive business insights.</li>
<li>Design, Monitor and optimize data pipelines and infrastructure: Analyze performance metrics, identify bottlenecks, and implement optimizations for efficiency and scalability.</li>
<li>Collaborate with cross-functional teams: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations.</li>
<li>Stay ahead of the curve: Continuously learn and adapt to the evolving landscape of big data technologies and best practices.</li>
<li>Lead the Databricks partnership: Own the day-to-day relationship, coordinate joint account planning, support enablement and certifications, and contribute to joint propositions and go-to-market activity.</li>
<li>Support pre-sales activity: Lead/assist discovery workshops, define solution options and reference architectures, contribute to estimates and delivery approaches, and help produce high-quality proposals and presentations.</li>
<li>Be a Databricks champion or on the pathway to become one</li> 
</ul></div></div><div><div><h2 class="jobSectionHeader">What You'll Bring</h2> 
</div><div>You will bring deep experience delivering data platforms and data architecture within complex public sector environments, with a strong understanding of government operating models, regulatory obligations, and the need for trusted, mission critical data. You will have a proven ability to design secure, scalable, and well governed data foundations that support analytics, AI, and GenAI while meeting requirements for data protection, sovereignty, transparency, and auditability. You will be comfortable working with senior stakeholders to translate outcomes into pragmatic data and AI architectures, balancing innovation with risk management. You will bring strong leadership and collaboration skills, enabling multi supplier delivery teams to align around shared standards, reuse platforms effectively, and build sustainable data capabilities that deliver long term value for citizens and public services. 
 
Experience:
<ul><li>Minimum 7+ years of experience as a Data Architect with experience in designing, developing and implementing Databricks solutions</li>
<li>Proven expertise in Databricks, Apache Spark, and data platforms with a strong understanding of data warehousing concepts and practices.</li>
<li>Experience designing and delivering data platforms on at least one major cloud provider (AWS, Azure and/or GCP preferred).</li>
<li>Experience working in pre-sales roles, including shaping opportunities, producing estimates, and contributing to proposals and client presentations.</li>
<li>Experience leading or contributing to vendor alliances/partnerships (ideally Databricks), including joint proposition development and go-to-market activity.</li>
<li>Excellent problem-solving and analytical skills and strong communication and teamwork skills.</li>
<li>Passion for data and a thirst for learning and is either already a Databricks champion or working towards it</li>
<li>Relevant architecture certifications from Databricks and/or cloud providers.</li> 
</ul></div></div><div><div><h2 class="jobSectionHeader">Additional Information</h2> 
</div><div>Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
If you are successfully offered this position, you will go through a series of pre-employment checks, including identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service) 
What we&rsquo;ll offer you 
You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.
You will be empowered to explore, innovate, and progress. You will benefit from Capgemini&rsquo;s &lsquo;learning for life&rsquo; mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more. 
 
Why we&rsquo;re different 
At Capgemini, we help organisations across the world become more agile, more competitive, and more successful. Smart, tailored, often ground-breaking technical solutions to complex problems are the norm. But so, too, is a culture that&rsquo;s as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too.
 
 
Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age, and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.</div></div></div></div></div></div></div>

Databricks Data Solution Architect

Salt

<div>
 
 
 Role: Cloudera Technical Architect
 
 
 
 
 Location: Jeddah
 
 
 
 
 Program:
 
 Enterprise Data Lakehouse Implementation (Expansion, Remediation &amp; Operationalization)
 
 
 
 Domain:
 
 Banking &amp; Financial Services (BFSI)
 
 
 
 Immediately available candidate preferred
 
 
 
 
 
 
 My client is a global leader in IT services, consulting, and business solutions.
 
 
 
 
 
 
 Role Summary
 
 
 
 My client is seeking an experienced Cloudera Technical Architect to lead the design, optimization, and governance of a large-scale Enterprise Data Lakehouse platform. The role will focus on ensuring platform scalability, security, performance, and operational excellence while supporting remediation of existing implementations and future expansion initiatives.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design and govern Cloudera CDP architecture aligned with enterprise Data Lakehouse standards.
 </li>
 <li>
 Define architecture patterns for batch, streaming, and analytics workloads.
 </li>
 <li>
 Lead performance optimization across Spark, Hive, Impala, and YARN environments.
 </li>
 <li>
 Architect and support real-time data ingestion using Kafka and NiFi.
 </li>
 <li>
 Implement and enforce security controls using Ranger, Kerberos, encryption, and access governance.
 </li>
 <li>
 Review existing Cloudera implementations, identify gaps, and drive remediation initiatives.
 </li>
 <li>
 Define monitoring, high availability, disaster recovery, and operational best practices.
 </li>
 <li>
 Collaborate with architects, engineering teams, and business stakeholders to ensure successful platform delivery.
 </li>
 </ul>
 
 
 
 
 
 Required Skills
 
 
 <ul>
 <li>
 Strong expertise in Cloudera Data Platform (CDP)
 </li>
 <li>
 Hands-on experience with:
 </li>
 <li>
 HDFS, Spark, Hive, Impala
 </li>
 <li>
 Kafka, NiFi
 </li>
 <li>
 Ozone, HBase, Kudu
 </li>
 <li>
 Iceberg, Hive Metastore
 </li>
 <li>
 Ranger, Knox, Kerberos
 </li>
 <li>
 Cloudera Manager and Cloudera AI
 </li>
 <li>
 Strong knowledge of cluster sizing, capacity planning, workload management, and performance tuning.
 </li>
 <li>
 Experience implementing secure, highly available, enterprise-scale data platforms.
 </li>
 </ul>
 
 
 
 
 
 Experience
 
 
 <ul>
 <li>
 10&ndash;15+ years of experience in Big Data and Data Platform technologies.
 </li>
 <li>
 Proven experience architecting and optimizing large-scale Cloudera environments.
 </li>
 <li>
 
 
 Banking/BFSI or other regulated industry experience preferred.
 
 
 </li>
 <li>
 Experience working with onsite and offshore delivery teams.
 </li>
 </ul>
 
 
 
 
 *** Only successful candidates will be contacted ***
 
</div>

Cloudera Technical Architect

Deutsche Börse Group

<div>
 Your career at Deutsche B&ouml;rse Group
 
 Your area of work:
 
 
 
 As a Data Architect at Clearstream Securities Services, you will play a key role in driving our digital transformation by shaping the data architecture that underpins strategic initiatives such as Data &amp; AI, the D7 digital securities platform, the modernization of our Digital CSD, and our cloud adoption journey. Your work will ensure that Clearstream&rsquo;s data ecosystem is secure, scalable, and future-ready, enabling advanced analytics, regulatory compliance, and innovative services for global financial markets. By defining enterprise standards and collaborating across domains, you will help position Clearstream as a leader in digital finance and data excellence.
 
 
 
 Your responsibilities:
 
 
 
 
 <ul>
 <li>
 Define the target-state cloud data architecture (Lakehouse) across BI, analytics, and ML&mdash;including reference architectures, patterns, and guardrails.
 </li>
 <li>
 Lead domain-driven and Data Mesh architecture: curate federated data product standards, contracts, and interoperability guidelines.
 </li>
 <li>
 Establish architecture decision records (ADRs) and technology roadmaps (near/mid/long term), aligning with enterprise data strategy and regulatory requirements.
 </li>
 <li>
 Act as a trusted advisor to data scientists, analysts, and business product teams; unlock self-service patterns and reuse.
 </li>
 <li>
 Lead onboarding, training, and enablement programs to scale platform and catalog adoption; raise data literacy across domains.
 </li>
 <li>
 Mentor engineers and stewards; foster a culture of automation, reliability, and measurable outcomes.
 </li>
 <li>
 Guide the design and configuration of Atlan workspaces, clusters, compute policies, and libraries; ensure high availability, scalability, and cost efficiency.
 </li>
 <li>
 Own enterprise metadata strategy&mdash;ingestion, enrichment, and stewardship&mdash;leveraging Atlan (or equivalent) for catalog, lineage, glossary, and data contracts.
 </li>
 <li>
 Define data quality frameworks (profiling, rules, SLAs, monitoring) using solutions like Soda/Great Expectations; embed DQ controls into pipelines.
 </li>
 <li>
 Establish critical data element (CDE) standards, certification workflows, and KPIs; publish management reporting on catalog adoption and DQ outcomes.
 
 
 
 </li>
 </ul>
 
 Your profile:
 
 
 
 
 <ul>
 <li>
 8&ndash;12+ years in data architecture/engineering within cloud big data platforms (GCP preferred), including enterprise and regulated environments.
 </li>
 <li>
 Proven leadership in Databricks/Spark, Lakehouse architectures, and operationalizing Unity Catalog at scale.
 </li>
 <li>
 Hands-on track record with metadata/catalog platforms (Atlan/Collibra) and data quality frameworks (Soda/Great Expectations), including enterprise rollout and adoption.
 </li>
 <li>
 Demonstrated success aligning IT, business, compliance, and security to implement governed, high-quality data solutions.
 </li>
 <li>
 Deep understanding of data modeling, data contracts, DQ SLAs, lineage, privacy/security, and observability (e.g., Azure Monitor/Datadog).
 </li>
 <li>
 Working knowledge of ML lifecycle (MLflow, feature stores) and semantic/metrics layers for analytics products.
 </li>
 <li>
 Executive-level communication, stakeholder engagement, and influence; comfortable with board-level reporting and audit dialogue.
 </li>
 <li>
 Strong facilitator and coach; able to drive consensus across diverse technical and business teams.
 </li>
 <li>
 Fluent in English; additional language skills are a plus.
 </li>
 <li>
 Certifications (preferred)
 </li>
 <li>
 Azure Data Engineer/Architect; Databricks Data Engineer Professional/Architect; TOGAF; CDMP (DAMA); Security/Compliance certifications are advantageous.
 
 </li>
 </ul>
</div>

Senior Data Architect (f/m/d)

TouMetis

<div>Principal Data Architect / Head of Data Engineering

Location: Hybrid (1-2 days in the office a week) 
Type: Full-time 
Reports to: Vice President, Data Science

Role Overview

We are seeking a hands-on Principal Data Architect to own and evolve our end-to-end data platform as the company scales. This role sits at the intersection of data engineering, data architecture, and data management, acting as the critical link between our Data Science and Cloud Engineering teams.

Today, our core data infrastructure is tightly coupled to our product UI and optimized for transactional workflows. While this has served us well, it limits extensibility, analytical flexibility, and scalability. Your mission is to architect data as a first-class product&mdash;one that is observable, queryable, versioned, and reusable by clients and internal teams alike.

This is not a pure strategy role. You will advise, design, and implement, working hands-on with Python, SQL, and infrastructure-as-code while influencing architectural decisions across the organization.

What You&rsquo;ll Do

Own the Data Platform Vision
<ul>
<li>Define and champion a scalable, secure, and extensible data architecture aligned with company growth.</li>
<li>Set standards, principles, and ways of working for data architecture, DataOps, and governance.</li>
<li>Ensure data models, pipelines, and storage systems support both product needs and advanced analytics/ML use cases.</li>
</ul>
Bridge Data Science &amp; Cloud Engineering
<ul>
<li>Act as the primary interface between data science and cloud engineering teams.</li>
<li>Translate analytical and ML needs into production-ready data architectures.</li>
<li>Prototype and productionize data solutions collaboratively across disciplines.</li>
</ul>
Build Data as a Product
<ul>
<li>Design and implement curated, versioned datasets with clear data contracts and lineage.</li>
<li>Enable feature creation, reuse, and publication for low-latency serving and batch inference.</li>
<li>Improve data observability, quality monitoring, alerting, and health checks across the platform.</li>
</ul>
Architect for Scale &amp; Cost Efficiency
<ul>
<li>Work with Toumetis&rsquo; Principal Cloud Engineer to evaluate and advise on cloud data technologies (e.g. Snowflake, Databricks, Redshift, Azure Data Services), balancing cost, performance, and long-term flexibility.</li>
<li>Challenge existing constraints and design patterns pragmatically, appropriate to a small but growing company.</li>
<li>Design data flows and lifecycle management from ingestion to consumption.</li>
</ul>
Enable Advanced Analytics &amp; ML
<ul>
<li>Partner with the data science and software development teams to establish strong MLOps and DataOps practices.</li>
<li>Support geospatial and large-scale analytical workloads.</li>
<li>Ensure data is discoverable, reusable, and fit for experimentation and production ML.</li>
</ul>
Governance &amp; Client Engagement
<ul>
<li>Develop a streamlined Enterprise Data Management (EDM) and data governance roadmap.</li>
<li>Ensure governance supports&mdash;not blocks&mdash;innovation and strategy changes.</li>
<li>Contribute to solution design with clients, including pre-sales, technical presentations, and strategy sessions.</li>
</ul>
Key Responsibilities
<ul>
<li>Create conceptual, logical, and physical data models across multiple subject areas.</li>
<li>Define data architecture frameworks, standards, and policies.</li>
<li>Map and manage data flows across systems and teams.</li>
<li>Advise on or lead procurement and implementation of data platforms and tooling.</li>
<li>Build interactive analytics solutions and guide clients to actionable insights.</li>
<li>Support traditional and modern data platforms (SQL Server, cloud data warehouses, big data ecosystems).</li>
</ul>
What We&rsquo;re Looking For

Experience
<ul>
<li>~7+ years working with business and technology stakeholders on data architecture and analytics initiatives.</li>
<li>Proven experience designing and delivering scalable data platforms in cloud environments.</li>
<li>Strong hands-on experience with Python, SQL, and infrastructure-as-code.</li>
<li>Experience across major cloud providers (AWS, Azure, or GCP).</li>
<li>Familiarity with modern data platforms (e.g. Snowflake, Databricks, Redshift, Hadoop ecosystems).</li>
<li>Solid understanding of data science and machine learning workflows and their infrastructure pain points.</li>
<li>Experience with Microsoft data platforms (SQL Server, Power BI, Azure Data Services) is a plus.</li>
</ul>
Mindset &amp; Skills
<ul>
<li>A DataOps-first mindset: lineage, versioning, data contracts, and automation by default.</li>
<li>Comfortable challenging existing architectures and proposing pragmatic alternatives.</li>
<li>Strong systems thinker who understands when to apply different data modeling patterns.</li>
<li>Self-starter who thrives in ambiguity and small-team environments.</li>
<li>Passionate about solving problems with data and staying current with emerging tools and practices.</li>
<li>Strong communicator, able to influence engineers, data scientists, and clients alike.</li>
</ul>
Why This Role Matters

This role is foundational to our next phase of growth. You will define and improve how data is built, governed, and consumed across the company&mdash;ensuring it is scalable, observable, and future-proof, while remaining practical for a small, fast-moving team.

If you enjoy owning data end-to-end, bridging disciplines, and building platforms that unlock real business and analytical value, we&rsquo;d love to talk.</div>

Principal Data Architect

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
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 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
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 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
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 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
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 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
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 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
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 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
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 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
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 Ensure platform reliability through monitoring, alerting, and structured incident response.
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 AI/ML &amp; Analytics Enablement
 
 
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 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
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 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
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 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
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 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
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 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
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 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
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 Support regulatory, ethical, and internal compliance obligations across the data estate.
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 Cloud &amp; Cost Discipline
 
 
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 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
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 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
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 Collaboration &amp; Technical Leadership
 
 
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 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
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 Provide hands-on technical guidance and code review across the team.
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 Translate business requirements into technical designs with clear delivery outcomes.
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 Required Qualifications
 
 
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 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
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 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
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 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
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 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
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 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
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 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
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 Practical FinOps outcomes on cloud spend.
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 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
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 Excellent written and verbal communication skills across technical and business audiences.
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 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
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 Direct experience of a Synapse Analytics to Databricks migration.
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 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
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 Familiarity with Power BI semantic models and enterprise BI governance.
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 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
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 Multi-entity, multi-country group exposure with mixed data residency considerations.
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 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
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 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
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 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
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 </ul>
 
 
 Preferred (one or more):
 
 
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 Databricks Certified Machine Learning Professional
 
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 Databricks Certified Generative AI Engineer Associate
 
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 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
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 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
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 Microsoft Certified: Azure Solutions Architect Expert
 
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 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
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 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
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Data Platform Lead

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