At a Glance
- Tasks: Lead the design and optimisation of enterprise-scale data platforms and analytical solutions.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Flexible working, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with mentorship opportunities and career advancement.
- Why this job: Make a real impact by transforming complex data into actionable insights.
- Qualifications: 10+ years in data architecture, strong expertise in cloud platforms and data modelling.
The predicted salary is between 72000 - 88000 £ per year.
Job Summary onsite SR for Amit Mishra replacement.
- Job Title
- Senior Data Analyst / Data Architect
Experience
10+ Years
Role Summary
We are seeking an experienced
Senior Data Analyst / Data Architect to lead the design, development, and optimization of enterprise-scale data platforms and analytical solutions.
The ideal candidate will possess strong expertise in data modeling, cloud data warehousing, business analytics, and modern data engineering practices.
This role requires close collaboration with business stakeholders, architects, analysts, and engineering teams to transform complex business requirements into scalable and performant analytical solutions.
Key Responsibilities
Key Responsibilities
- Data Architecture & Design
- Design and implement enterprise-grade data architectures supporting analytics, reporting, and AI/ML initiatives.
- Develop conceptual, logical, and physical data models aligned with business requirements.
- Establish scalable dimensional, semantic, and canonical data models for enterprise reporting.
- Define data standards, governance principles, and best practices across the data ecosystem.
- Lead architecture reviews and ensure adherence to enterprise architecture standards.
- Analytics Engineering
- Build and maintain scalable, reusable, and modular data models using dbt and Snowflake.
- Transform legacy data assets and complex database views into optimized cloud-native analytical structures.
- Develop curated semantic layers to enable self-service analytics and business intelligence.
- Implement automation for data transformations, testing, deployment, and monitoring.
- Data Analysis & Business Insights
- Partner with business stakeholders to understand analytical requirements and define KPIs.
- Translate business problems into data solutions and actionable insights.
- Perform advanced analysis of large datasets and provide strategic recommendations.
- Support executive dashboards, operational reporting, and performance measurement frameworks.
- Drive data-driven decision making through high-quality analytical outputs.
- Data Quality & Governance
- Define and implement data quality frameworks, validation rules, and monitoring processes.
- Establish metadata management, data cataloging, and lineage practices.
- Ensure compliance with data governance, security, privacy, and regulatory standards.
- Develop policies for master data management and data stewardship.
- Performance Optimization
- Optimize Snowflake storage, compute resources, and warehouse configurations.
- Improve query performance, data loading processes, and reporting response times.
- Monitor platform utilization and recommend cost optimization strategies.
- Implement access controls, role-based security, and attribute-based access control (ABAC).
- Leadership & Collaboration
- Mentor junior analysts, engineers, and data modelers.
- Lead technical workshops, design discussions, and architecture reviews.
- Collaborate with product owners, business users, data scientists, and engineering teams.
- Act as a trusted advisor for data strategy and modernization initiatives.
- Skill Requirements
- Technical Requirements
- Core Platforms
- Expert-level experience with
Snowflake Cloud Data Platform .
- Strong hands-on expertise in dbt Core and dbt Cloud .
- Experience with modern cloud platforms such as AWS, Azure, or GCP.
- Familiarity with data orchestration tools such as Airflow, Azure Data Factory, or AWS Glue.
- Data Modeling Expertise
- Dimensional Modeling (Kimball Methodology).
- Semantic Layer Design and Business Metrics Modeling.
- Data Vault and Enterprise Data Warehouse concepts.
- Logical, Physical, and Canonical Data Modeling.
- Star Schema and Snowflake Schema design.
- Analytics & BI
- Power BI, Tableau, Looker, or equivalent BI platforms.
- KPI framework development and executive dashboard design.
- Advanced SQL and analytical problem-solving.
- Business requirements gathering and stakeholder management.
- Data Engineering
- ETL/ELT design and implementation.
- Data pipeline development and optimization.
- Data quality validation and automated testing.
- Batch and near real-time data processing concepts.
- Software Engineering Practices
- Git-based source control and branching strategies.
- CI/CD pipeline implementation.
- Automated testing frameworks.
- Agile and Dev Ops methodologies.
- Infrastructure-as-Code knowledge is a plus.
- Other Requirements
Data Architect employer: HCL Tech
As a leading employer in the data architecture space, we offer a dynamic and collaborative work environment that fosters innovation and professional growth. Our flexible hybrid work model allows you to balance your personal and professional life while working on cutting-edge projects that drive impactful business insights. With a strong commitment to employee development, mentorship opportunities, and a culture that values diversity and inclusion, we empower our team members to excel and make meaningful contributions to our enterprise-scale data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Architect
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like HCL Tech!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Architect at HCL Tech.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like HCL Tech.
✨Apply Directly through Our Website
When you find a suitable opening like Data Architect at HCL Tech, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Architect
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at HCL Tech, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at HCL Tech. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at HCL Tech
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at HCL Tech!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
