6 days ago
Hyderābād, IndiaStaff+
Responsibilities
- Develop, document, and maintain the future-state architecture for the Data Platform.
- Provide architectural oversight and technical guidance across storage and access, orchestration, and data acquisition domains.
- Partner with execution teams to translate strategy into implementation and actionable technical roadmaps.
- Align Commercial Data’s technical strategy with Enterprise Architecture standards and the broader architectural vision.
- Lead the creation, review, and governance of Architecture Decision Records.
- Establish architectural patterns for data governance, metadata management, semantic layers, and data quality.
- Drive the architectural vision for AI-enabled data access using LLMs and generative AI.
- Lead technical design reviews, mentor senior engineers and technical leads, and help grow technical capabilities.
- Evaluate technologies and platforms while promoting scalable, pragmatic, and maintainable solutions.
Requirements
- 10+ years of software engineering experience with deep expertise in data engineering, data platforms, and data infrastructure.
- Proven experience as a software architect or principal engineer designing large-scale data systems and platforms.
- Hands-on experience with ETL/ELT systems and orchestration tools such as Apache Airflow, Prefect, or Dagster.
- Strong experience with AWS cloud infrastructure and services including S3, Glue, EMR, Lambda, Step Functions, and EventBridge.
- Deep understanding of data lakehouse architectures and experience with Databricks or Snowflake.
- Proficiency in Python and relevant data engineering libraries.
- Experience developing architectural vision, technical roadmaps, Architecture Decision Records, and governance practices.
- Ability to collaborate with and influence diverse technical and business stakeholders.
- Experience mentoring senior engineers and developing team capabilities.
- Understanding of data governance, metadata management, data quality frameworks, and data privacy regulations.
- Desired qualifications include Databricks experience with Delta Lake, Unity Catalog, and Databricks workflows; AI/ML, LLM, generative AI, semantic layer, knowledge graph, metadata platform, data catalog, streaming, Apache Iceberg, vector database, RAG, DataOps, platform engineering, financial services, FinOps, data mesh, data fabric, and relevant certification experience.
- Experience with Kafka or Kinesis, market data systems, open-source or conference contributions, cloud cost optimization, and AWS or Databricks certifications is preferred.
Benefits
- Health, life, and disability insurance.
- Retirement savings plans and a discounted employee stock purchase program.
- Paid holidays, family leave, and company-wide wellness days.
- Flexible work accommodations supporting work/life harmony.
- Career progression planning with dedicated monthly learning and development time.
- Business Resource Groups, volunteerism and sustainability programs, and a global collaborative community.
Tech Stack
Categories
Data Engineering
About FactSet
FactSet builds a financial data and analytics platform used by asset managers, investment banks, hedge funds, and wealth managers for research, portfolio management, trading, and risk. Its products include the FactSet workstation, data feeds and APIs, and workflow tools like OMS/EMS, sold primarily via subscription licensing. Founded in 1978 and headquartered in Norwalk, Connecticut, FactSet is a public company listed on the NYSE (ticker: FDS).