- 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 modelstraditional teams, pools, or podsare tailored to each clients 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 :