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LSEG

Global financial market infrastructure and data

Senior Engineering Manager - Data

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A substantial track record of designing, building, shipping, operating, and evolving production software applications, services, platforms, or libraries over multiple years.
  • Production-level expertise in Python, or equivalent depth in Java, C#, C, C++, Scala, Go, or Rust, with motivation to make Python the primary language.
  • Depth in software design and architecture, including decomposing complex problems, choosing appropriate boundaries and patterns, and explaining design decisions.
  • Ability to write and review high-quality code, using Python type hints, linters, and pytest discipline, or equivalent rigor in another language.
  • Willingness to remain hands-on and lead through code.
  • Proven experience mentoring and developing engineers through code review, pairing, design guidance, and standards-setting.
  • Strong ownership of technical outcomes and production behavior.
  • Deep relational database experience, including data modeling, performance, and evolution under real workloads.
  • Solid AWS experience and strong CI/CD, automation, and testing practices.
  • Comfort with data-intensive systems, including batch processing, ETL, schema evolution, and correctness at scale.
  • Ability to communicate design decisions to technical and non-technical audiences and build shared understanding.
  • Ability to collaborate and work effectively in Agile teams.

Responsibilities

  • Design and write production code, primarily in Python, and set quality standards through shipped code.
  • Own technical direction and architecture for a defined platform area, making trade-offs explicit.
  • Lead the design of software systems, including services, APIs, shared libraries, and interfaces, with resilience, performance, and reusability built in.
  • Drive engineering quality through code reviews, reusable shared components, testing, refactoring, and secure development practices.
  • Mentor and coach engineers through pairing, reviewing, and developing their capabilities.
  • Assess design and risk trade-offs involving failure modes, operational readiness, security, and cost, and remove blockers.
  • Design data-intensive software using relational databases such as Aurora PostgreSQL, object storage, and AWS services, with attention to schema design and evolution at scale.
  • Build software that processes data at scale on AWS using Lambda, containerized services, and, where appropriate, Glue, EMR Serverless, and formats such as Apache Iceberg.
  • Embed observability and quality controls to identify issues before they affect customers.
  • Collaborate across teams and translate between technical and non-technical audiences.
  • Build knowledge of the financial indices domain and apply it to team-level design.

Desired Qualifications

  • Apache Spark or PySpark experience and experience optimizing large-scale distributed processing.
  • Experience designing systems for datasets and workloads beyond single-machine scale.
  • Experience with Scala, Java, C++, Go, or Rust in data-intensive and performance-critical systems, and judgment about when to use them.
  • Experience with Apache Iceberg, Delta Lake, or similar open table formats, and lakehouse architecture.
  • Experience with Databricks, Snowflake, or comparable data platforms.
  • Experience with CI/CD tools such as GitLab CI, Jenkins, or GitHub Actions.
  • Experience with infrastructure as code such as Terraform or CDK, and platform or DevOps work.
  • Experience with data quality frameworks such as Great Expectations or Deequ.
  • Experience in financial markets, index data, or investment analytics.
  • Experience in finance, including investment banking or asset or portfolio management, or in a product company.

About the Company

LSEG

Global financial market infrastructure and data

LSEG provides global financial market infrastructure and data across the full value chain. It delivers data, analytics, and risk-management tools, benchmarks via FTSE Russell, regulatory and financial crime risk services, and trading, clearing, and settlement through its Capital Markets and Post Trade divisions, typically accessed via subscriptions, licensing, and fees. The company differentiates itself by offering an integrated, end-to-end platform that covers pre-trade data and analytics to post-trade processing with a broad, global footprint. Its goal is to grow over the long term by leveraging its diversified portfolio and international reach to create value for shareholders and customers.

Company size
10,001+
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1801

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