Solution Architect

Your role

About Us

Atlas Copco is a Swedish multinational industrial company that was founded in 1873 headquartered in Nacka, Sweden. We are world leaders in Compressors; we also manufacture industrial tools and equipment.

We are an IT Service Provider company within Atlas Copco Group called Global IT Hub (India). We are also focusing on Digital transformation Technologies for Data Driven Decisions, Web and Applications developments, Automations, IT Infrastructure etc.

Data Analytics Competence is the competence within the Global IT Hub (India).

Job Description

We are seeking a highly skilled and experienced Solution Architect to join our growing Data & Aanlytics team from Digital Technology vertical. In this role, you will play a pivotal role in designing, developing, and implementing innovative data solutions that support our data analytics initiatives. You will bridge the gap between business needs and technical feasibility, ensuring our data infrastructure is scalable, secure, and optimized for advanced analytics.

The Role

Bridges the gap:
Translates business needs into technical solutions for data analytics projects.
Designs the roadmap:
Define and implement scalable, secure data architectures for analytics platforms and BI solutions.
Technology expertise:
Possesses deep knowledge of various data technologies (cloud platforms, data lakes, data warehouses, analytics tools) to recommend the best fit for optimal performance.
Integration champion:
Designs solutions that integrate seamlessly with existing IT infrastructure.
Scalability focus:
Keeps scalability and future growth in mind when designing the architecture.
Collaboration king:
Works closely with data engineers, analysts, data scientists, and stakeholders to ensure everyone's on the same page.
Risk assessment:
Identifies potential risks and proposes solutions to mitigate them.
Communication is key:
Clearly communicates complex technical concepts to both technical and non-technical audiences.

Innovation: Stays at part with emerging trends in data and analytics to future-proof solutions.

Key Responsibilities And Accountabilities

Skills and Experience

Data Modelling & Design:
Expertise in data modelling techniques, including relational (SQL) and non-relational (No

SQL) databases.
Data Warehousing & ETL:
Solid understanding of data warehousing concepts, ETL (Extract, Transform, Load) processes, and big data technologies.
Programming

Languages:

Proficiency in SQL and potentially scripting languages like Python, Spark, etc. for data manipulation and automation.
Cloud Platforms:
Knowledge of cloud platforms (Microsoft Azure, Data Bricks, Fabric) for deploying and managing data solutions.
Data Management & Security:
Understanding of data governance, security best practices, and data access controls.

Certifications:

good to have relavent certifications which shows academic regor e.g., Microsoft Certified:
Azure Solutions Architect Expert, Databricks Certified Solution Architect

To succeed, you will need

Competences

Communication &

Collaboration:

Excellent communication skills to bridge the gap between technical and non-technical stakeholders.
Problem-Solving & Critical Thinking:
Ability to analyze complex data problems and design effective solutions.
Project Management:
Experience managing data-related projects and ensuring successful execution.
Teamwork:
Ability to guide & collaborate effectively with data engineers, analysts, data scientists, and business teams.
Strategic thinking and Enterprise-level solution design

Stakeholder management

You can discuss with stakeholders about their requirements and clearly communicate back your understanding of the requirements.
You can work with the stakeholders to understand the big picture and work towards it.
Work with team members and other users from the organization at different levels for performance improvement and suggestions.

Must have

Communication skills, Facilitation:
Excellent communication skills to bridge the gap between technical and non-technical stakeholders (business users, data engineers, analysts, data scientists).

Collaboration:

Ability to work effectively in a team environment, fostering collaboration and knowledge sharing across the data team.
Analytical Thinking:
Strong ability to analyse complex business needs and translate them into technical solutions for data analytics projects.
Technical Architecture Design:
Skilled at designing and implementing scalable data pipelines, platforms, and tools to support data analytics at an enterprise level.
Technology Selection:
Deep knowledge of various data technologies (cloud platforms, data lakes, data warehouses, analytics tools) to recommend the best fit for specific needs.

Nice to have

Emerging Technologies:
Curiosity and interest in keeping up with emerging data technologies.
Experience in hybrid environments: cloud + on-prem
Business Acumen:
Understanding of core business processes and how data analytics can drive strategic decision-making.
Project Management Tools:

Experience with project…