Data Architect (Cloud, ETL, Python) || 7-12 yrs

Iklavya; Dadri; On-site; INR 2,000,000 - 2,500,000; Full time

Job summary

A leading technology consulting firm in India seeks a seasoned Data Architect. In this role, you will lead data migration projects and develop scalable cloud solutions while ensuring data quality and security. Ideal candidates will have at least 10 years of industry experience, including expertise in ETL processes and cloud platforms (AWS, Azure, GCP). Strong problem-solving abilities and excellent communication skills are essential for collaborating with cross-functional teams in an agile environment.

Qualifications

• 10+ years of industry experience in database solution development and architecture.
• Experience in leading technical teams in migration or cloud adoption projects.
• Proficiency in SQL, Python, and/or Scala for data engineering.

Responsibilities

• Develop ETL pipelines for data migration and transformation.
• Ensure data integrity, quality, and security during migration.
• Design scalable cloud-native data solutions.

Skills

SQL

Python

Data migration

Cloud architecture

Data governance

Education

BE/B.Tech/M.C.A./M.Sc (CS)

Tools

Informatica

Talend

Apache NiFi

AWS

Azure

GCP

Job description

Lead discussions with business and functional analysts to understand requirements and assess integration impacts on business architecture. Prepare technical architecture and design, clarify requirements, and resolve ambiguities. Develop solutions in line with established technical designs, integration standards, and quality processes. Create and enforce technical design and development guides, templates, and standards. Facilitate daily scrum meetings, manage deliverables, and prepare weekly status reports for leadership review. Conduct detailed deliverable reviews and provide technical guidance to team members. Collaborate with onsite clients, coordinators, analysts, and cross-functional teams. Design templates or scripts to automate routine development or operational tasks.

Analyze legacy data sources and architect migration strategies to modern platforms (e.g., cloud databases, data lakes).

Develop ETL (Extract, Transform, Load) pipelines to move and transform data efficiently.

Ensure data integrity, quality, and security throughout the migration process.

Design and implement scalable, cloud-native data solutions (e.g., AWS, Azure, GCP).

Build and maintain data models, APIs, and microservices that support modernized applications.

Collaborate with application developers to ensure seamless data access and performance.

Evaluate existing data infrastructure, identifying technical debt and modernization opportunities.

Document data flows, dependencies, and business logic embedded in legacy systems.

Tune data pipelines and storage solutions for speed, reliability, and cost-effectiveness.

Implement monitoring and alerting data operations.

Work closely with business analysts, application architects, and cloud engineers.

Translate business requirements into technical data solutions.

Provide guidance and best practices for data modernization.

Develop, test, and refine prompts to elicit desired responses from AI models.

Experiment with prompt structures, context windows, and input formatting to improve output quality.

Test and compare different models and APIs to select the best fit for specific tasks.

The team:

Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models—traditional teams, pools, or pods—are tailored to each client’s needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Qualifications

Must Have Skills/Project Experience/Certifications:

• 10+ years of industry experience, with at least 6+ years in database solution development, architecture, and programming, with a focus on data migration or modernization projects.
• At least 4 years’ experience leading technical teams in database migration, modernization, or cloud adoption projects.
• Demonstrated expertise in executing full data migration lifecycles, including requirements gathering, planning, schema conversion, data transformation, migration, and validation for large-scale systems.
• Hands‑on experience with relational database systems (such as DB2, Oracle, MS SQL, PostgreSQL), including schema design and optimization.
• Proficiency in SQL, Python, and/or Scala for data engineering tasks.
• Experience with ETL tools (e.g., Informatica, Talend, Apache NiFi).
• Experience with scripting languages for data extraction, transformation, automation, and performance benchmarking (shell scripting, Windows PowerShell, PySpark ).
• Hands‑on experience with cloud platforms (AWS, Azure, GCP) and their data services.
• Familiarity with big data technologies (e.g., Spark, Hadoop) and data warehousing (e.g., Snowflake, Redshift).
• Proven track record in migrating legacy data systems to cloud or modern architectures.
• Understanding data governance, security, and compliance in modernization contexts.
• Strong problem‑solving and analytical abilities.
• Excellent communication and collaboration skills.
• Ability to work in agile, cross‑functional teams.
• Stay current with advancements in generative AI, LLMs, and prompt engineering techniques.
• Relevant certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate

Education:

BE/B.Tech/M.C.A./M.Sc (CS) degree or equivalent from accredited university.