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Engaged Employer

JPMorgan Chase & Co.

Compare

4.0

based on 6k Reviews

Video summary

Proud winner of ABECA 2024 - AmbitionBox Employee Choice Awards

Top Rated Mega Company - 2024

Top Rated Company for Women - 2024

Top Rated Financial Services Company - 2024

673 JPMorgan Chase & Co. Jobs

Lead Data Engineer

JPMorgan Chase

4.0

based on 6k Reviews

5-10 years

Bangalore / Bengaluru

1 vacancy

Lead Data Engineer

JPMorgan Chase & Co.

posted 9hr ago

Job Role Insights

Flexible timing

Key skills for the job

Python SQL GCP Data Governance Data Modeling Web Technologies

+ 3 more

Job Description

As a Lead Data Engineer at JPMorgan Chase within the Chase UK team, your primary responsibility will be to design and implement scalable data solutions with a particular emphasis on the ingestion and transformation stages. You will utilize cutting-edge technologies to address unique challenges and contribute to projects with wide-ranging impact. Your role will also involve working closely with diverse teams to guarantee data quality and availability, while promoting a culture of innovation and excellence.

Job Responsibilities

Design and implement complex, scalable solutions to process data and ensure timely availability for querying.
Develop reusable frameworks, prioritizing quality and long-term sustainability.
Thrive in a challenging environment and provide hands-on contributions across various projects.
Participate in regular code reviews to maintain code quality and adhere to best practices.

Required Qualifications, Capabilities, and Skills

Formal training or certification on Python concepts and 5+ years applied experience.
Extensive development experience using SQL.
Hands-on experience with MPP databases such as Redshift, BigQuery, or Snowflake, and modern transformation/query engines like Spark, Flink, Trino.
Familiarity with workflow management tools (eg, Airflow) and/or dbt for transformations.
Comprehensive understanding of modern data platforms, including data governance and observability.
Experience with cloud platforms (AWS, GCP, Azure).
Self-starter capable of delivering production-ready solutions with minimal supervision.
Strong SDLC practices, viewing data engineering as a software engineering discipline.
Solid theoretical fundamentals in topics such as database internals, distributed systems, and design patterns.

Preferred Qualifications, Capabilities, and Skills