Solutions Architect

Job Description – Solution Architect (Data Analytics)

Mindsprint Digital
Experience: 12–15 Years
Location: Chennai & Bangalore
Notice period: Immediate to 30 days

Role Overview
We are seeking an experienced Solution Architect to lead the design and implementation of enterprise-scale data analytics solutions. The ideal candidate will combine deep technical expertise in modern data platforms with strong business acumen, ensuring that Mindsprint Digital delivers scalable, secure, and innovative analytics capabilities to drive digital transformation.
Key Responsibilities
Architecture & Design
Define end-to-end architecture for data analytics platforms, including data ingestion, storage, processing, and visualization layers.
Design scalable solutions leveraging cloud-native services (Azure, AWS, GCP) and modern data platforms (Databricks, Snowflake, etc.).
Establish frameworks for data governance, metadata management, and security.
Solution Delivery
Collaborate with business stakeholders to translate requirements into technical solutions.
Guide engineering teams in implementing best practices for data pipelines, ETL/ELT, and advanced analytics.
Ensure solutions meet performance, scalability, and compliance standards.
Innovation & Strategy
Drive adoption of emerging technologies such as AI/ML, Generative AI, and real-time analytics.
Contribute to the data strategy roadmap, aligning architecture with business goals.
Evaluate new tools and platforms to enhance analytics capabilities.
Collaboration & Leadership
Partner with data engineers, scientists, and business analysts to deliver integrated solutions.
Provide technical leadership, mentoring, and architectural guidance to delivery teams.
Act as a trusted advisor to senior stakeholders on data-driven decision-making.
Mandatory Skills
12–15 years of experience in data engineering, analytics, and solution architecture.
Strong expertise in cloud platforms (Azure, AWS, GCP) and data platforms (Databricks, Snowflake, Hadoop ecosystem).
Hands-on experience with data modeling, ETL/ELT pipelines, and big data frameworks.
Proven track record in data governance, security, and compliance frameworks.
Strong knowledge of Python, SQL, and distributed computing frameworks (Spark, PySpark).
Excellent stakeholder management, communication, and leadership skills.
Good-to-Have Skills
Experience with AI/ML and Generative AI integration into analytics platforms.
Familiarity with MLOps practices and deployment of ML models at scale.
Exposure to real-time streaming platforms (Kafka, Azure Event Hub, AWS Kinesis).
Knowledge of BI tools (Power BI, Tableau, Qlik).
Certifications in cloud architecture (Azure Solutions Architect, AWS Certified Solutions Architect, GCP Professional Data Engineer).
Educational Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or related field.
Advanced certifications in cloud architecture or data engineering are highly desirable.