Data Engineer (Python Automation, SQL) at Intercontinental Exchange Holdings, Inc.

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

15 Sep, 26

Salary

0.0

Posted On

17 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, ETL/ELT Pipelines, PostgreSQL, MySQL, SQL Server, AWS, GCP, Apache Airflow, Power BI, Tableau, Web Scraping, Git, CI/CD, Generative AI, N8N

Industry

Financial Services

Description

Job Description Job Purpose Intercontinental Exchange (ICE) is seeking a highly motivated and detail-oriented Data Engineer to enhance Sustainable Finance Operations through automation and robust data quality practices. In this role, you will design and develop Python-based applications and data pipelines that ingest ESG documents and market data, store them in backend databases, perform rule-based and statistical validations, and deliver clean, reliable datasets for downstream products and operational workflows. Responsibilities Automation & Application Development: Design, develop, and maintain Python-based applications and ETL/ELT pipelines (e.g., ingest data from APIs and company websites, parse sustainability/ESG reports, and persist data in SQL backends). Database Engineering: Model operational tables; write optimized SQL queries (joins, window functions, CTEs); implement indexing and partitioning; and manage data migrations. Data Validation & Quality Control: Implement logical and business-rule validations for Sustainable Finance datasets to ensure accuracy and completeness. Workflow Orchestration: Schedule and monitor jobs using AWS/GCP orchestration tools (e.g., AWS Glue, Step Functions, GCP Dataflow) or similar; implement alerting and recovery runbooks. Data Visualization Support: Collaborate with Operations to publish curated datasets and build dashboards (Power BI/Tableau or equivalent) for tracking coverage, timeliness, and quality KPIs. Documentation & Traceability: Maintain comprehensive documentation—data lineage, validation rules, SLAs, and operational playbooks—to support audits and client transparency. Cross-Functional Collaboration: Work closely with Operations leads and product partners to resolve data issues, implement corrections, and continuously improve throughput and accuracy. Knowledge and Experience Bachelor’s or Master’s degree in computer science, Information Systems, Data Science, Business Analytics, or a related field. 2+ years of experience in Data Engineering or related roles with strong proficiency in Python (Pandas, Numpy, SQL Alchemy/pyodbc, OOPS) and production-grade SQL. Proven experience integrating Python applications with backend databases (PostgreSQL/MySQL/SQL Server), implementing CRUD operations, and managing batch/stream ingestion. Solid understanding of data quality techniques and auditability. Cloud & Workflow Orchestration Familiar knowledge with workflow orchestration tools (Apache Airflow, AWS Step Functions, or GCP Cloud Composer) to schedule, monitor, and recover data pipelines with alerting mechanisms in place. Familiarity with AWS or GCP cloud platforms to build and manage data pipelines, with exposure to big data frameworks and data transformation tools. Data Visualization & Web Data Acquisition Experience with data visualization tools (Power BI/Tableau or equivalent). Experience building web scrapping for company reports and implementing publication-date policies. Software Engineering Practices Knowledge of version control (Git), testing practices (unit tests), and CI/CD concepts. Generative AI & Automation Experience integrating Gen AI agents into existing ETL/ELT pipelines or operational data workflows. Proficiency with AI workflow automation platforms such as N8N. Hands-on experience with Generative AI concepts and familiarity with LLMs (e.g., Anthropic Claude, or open-source models) and their practical applications in data workflows.

Responsibilities

Design and develop Python-based applications and data pipelines to ingest and validate ESG and market data. Manage backend database engineering, workflow orchestration, and the creation of data visualization dashboards for quality tracking.