Expleo - Senior Data Architect (10-18 yrs)

Overview :

We are looking for an experienced and strategic Senior Data Architect to lead the design, modernization, and governance of enterprise-scale data platforms and architectures. The ideal candidate will have strong expertise in data engineering, cloud data ecosystems, enterprise integration, analytics, AI/ML data readiness, and modern data governance practices.

The role requires close collaboration with business stakeholders, enterprise architects, AI teams, engineering teams, and leadership to build scalable, secure, and high-performing data solutions that support digital transformation and advanced analytics initiatives.

Responsibilities :

- Define and implement enterprise-wide data architecture strategies, standards, and best practices.

- Design scalable data platforms, data lakes, data warehouses, and modern lakehouse architectures.

- Lead architecture discussions for cloud-based data ecosystems across AWS, Azure, or GCP.

- Design end-to-end data pipelines for structured, semi-structured, and unstructured data.

- Establish data governance, metadata management, lineage, security, and compliance frameworks.

- Work closely with AI/ML teams to enable high-quality data foundations for analytics and AI solutions.

- Define enterprise data models, master data management (MDM), and data integration strategies.

- Guide teams on ETL/ELT frameworks, streaming architectures, and real-time data processing.

- Collaborate with business stakeholders to translate business requirements into scalable technical solutions.

- Lead performance optimization, scalability planning, and cost optimization initiatives for data platforms.

- Evaluate and recommend new tools, technologies, and accelerators in the data and AI ecosystem.

- Provide technical leadership and mentoring to data engineers, developers, and architects.

- Ensure compliance with enterprise security, privacy, and regulatory requirements.

- Participate in solution estimation, proposal creation, architecture reviews, and customer discussions.

Qualifications :

- Bachelors or Masters degree in Computer Science, Information Technology, Data Science, or related field.

- Cloud certifications preferred :

1. AWS Certified Data Analytics

2. Azure Data Engineer / Solutions Architect

3. Google Professional Data Engineer

- TOGAF or enterprise architecture certifications are an added advantage.

Essential skills :

Technical Skills :

- Strong experience in enterprise data architecture and large-scale data platform implementation.

- Expertise in cloud platforms such as :

1. AWS (Redshift, Glue, EMR, Athena, S3)

2. Azure (Azure Data Factory, Synapse, Databricks, ADLS)

3. GCP (BigQuery, Dataflow, Dataproc)

- Strong knowledge of :

1. Data Warehousing

2. Data Lakes / Lakehouse Architecture

3. ETL / ELT frameworks

4. Data Modeling

5. Data Governance

6. Master Data Management

7. Metadata Management

- Experience with modern data engineering tools such as :

1. Databricks

2. Snowflake

3. Kafka

4. Spark

5. Airflow

6. dbt

- Strong SQL and database design expertise.

- Understanding of AI/ML data pipelines and analytics ecosystems.

- Experience with API integrations and enterprise integration patterns.

- Familiarity with DevOps/DataOps/MLOps practices.

Leadership & Functional Skills :

- Strong stakeholder management and communication skills.

- Experience leading distributed/global teams.

- Strong problem-solving and strategic thinking capabilities.

- Experience working in Agile delivery environments.

- Ability to drive architecture governance and technical decision-making