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Staff Data Architect

LM Wind Power Blades • Full-time • Bengaluru • 1w ago

Job Description Summary

Job Description

Job Description Summary

The individual will be responsible for Strategy & Architecture of LM Wind Power's Data platforms, Ingestions, reporting and advanced analytics to empower and enable business priorities. Knowledge in Azure cloud infrastructure, strong experience in Data Governance and enabling self-service. Being able to pilot and enable breakthrough technologies and push continuous improvements and automation in Operations;

Job Description - Essential Responsibilities

Data Architecture & Strategy Development:
- Design and implement scalable, resilient data architectures to support analytics, machine learning in Databricks, and operational applications.
- Define the long-term data strategy, architecture standards, and best practices aligned with organizational goals.
- Assess and recommend technologies and tools for data processing, storage, and management.
Data Modeling & Management:
- Develop and maintain logical and physical data models that reflect the business functional and processes.
- Ensure data integrity and high availability across various environments (on-premise - OT, cloud, and hybrid).
- Design and optimize ETL/ADF processes to move, transform, and store data efficiently.
- Strong demonstrated experience of reporting on Tableau, PowerBI and MS SSAS cubes
Data Governance & Security:
- Establish and enforce data governance policies, including data quality, lineage, and metadata management.
- Implement data security and privacy practices, ensuring compliance with regulations such as GDPR, HIPAA, and others.
- Collaborate with data engineering, security, and compliance teams to monitor data use and control access to sensitive data.
Cross-functional Collaboration & Support:
- Work with data scientists, analysts, engineers, and business stakeholders to gather requirements and translate them into data solutions.
- Guide cross-functional teams in best practices for data utilization and ensure alignment on data-related projects.
- Act as a technical mentor to data engineers and junior architects, providing guidance on data solutions and architectural approaches.
Performance Optimization & Troubleshooting:
- Analyze and improve data systems’ performance, reliability, and scalability.
- Troubleshoot and resolve issues in data pipelines, ensuring minimal downtime and impact on operations.
- Monitor and fine-tune database performance, storage costs, and processing speed.

Leadership:

Familiar with concepts of IT total cost of ownership. Works to assure work is on-time and within budget.
Delivers tasks on-time with alignment to architectural goals. Can identify and raise issues, risks and benefits.
Demonstrated working knowledge of internal organization
Foresee obstacles, identify workarounds, leverage resources, rally teammates.
Demonstrated ability to work with and/or lead blended teams, including 3rd party partners and customer personnel.
Proven analytical and problem resolution skills
Ability to influence and build consensus with other Information Technology (IT) teams and leadership

Personal Attributes:

Applies values, policies, procedures and precedent to make timely, routine decisions of limited, clear choice.
Reacts open-mindedly to new perspectives or ideas. Considers different or unusual solutions when appropriate.
Resolves day-to-day issues related to strategy implementation. Escalates issues that impact the client and/or strategic initiatives.

Qualifications:

Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field.
Experience: 8+ years of experience in data architecture, data engineering, or a related field, with a track record of architecting and deploying large-scale data solutions.
Note: Military experience is equivalent to professional experience

Technical Skills:
- Proficiency in data modeling tools and database technologies (e.g., SQL, NoSQL, columnar databases).
- Experience with cloud data platforms (e.g., AWS, Azure (preferred), Google Cloud) and data lake architectures.
- Strong programming skills in languages such as Python, SQL, and familiarity with ETL tools.
- Knowledge of data governance, data quality management, and regulatory compliance.
Soft Skills:
- Strong analytical and problem-solving skills, with the ability to translate complex business requirements into data architectures.
- Excellent communication skills, able to convey technical details to non-technical stakeholders.
- Leadership and mentorship abilities, with experience guiding junior team members.
Preferred Qualifications:
- Certification in data architecture or cloud platforms (e.g., Azure Data & Architecture).
- Knowledge of machine learning pipelines and MLOps.