Analytics Engineer - Associate at JPMC Candidate Experience page

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

09 Sep, 26

Salary

0.0

Posted On

11 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Modeling, Python, Snowflake, Databricks, Semantic Layer Design, KPI Definition, Dimensional Modeling, Data Quality Control, JSON Modeling, NoSQL Integration, Stakeholder Management, Performance Tuning, Data Documentation, BI Tooling, Orchestration Tooling

Industry

Financial Services

Description

You are a strategic thinker passionate about driving solutions in Analytics . You have found the right team. As a/an Associate Analytics Engineer within the Data & Analytics team, you will build analytics-ready data models and a trusted semantic layer that standardizes business metrics. You will translate stakeholder needs into governed datasets and KPI definitions in Snowflake and/or Databricks using SQL as the primary transformation language. You will embed data quality, documentation, and performance best practices so downstream teams can reliably reuse models for self-service reporting. JOB RESPONSIBILITIES * Lead development of dimensional and/or domain-oriented analytics data models optimized for BI and self-service consumption. * Design and maintain a semantic layer defining standardized metrics, dimensions, entities, and business definitions. * Translate stakeholder requirements into clear modeling deliverables, including grains, entities, metric logic, and acceptance criteria. * Build transformations primarily in SQL and leverage Python for complex logic, automation, and validation as needed. * Implement data quality controls, including tests, reconciliations, and anomaly checks tied to business-critical metrics. * Optimize model performance in Snowflake and/or Databricks by applying efficient joins and storage/performance strategies. * Collaborate with upstream teams to align source-to-model meaning, including semi-structured and NoSQL data considerations. * Establish modeling standards covering naming conventions, documentation, lineage, metric governance, and change management. * Document curated datasets and produce user guidance to enable correct adoption of semantic definitions. * Support consumers by troubleshooting metric questions and improving usability of downstream analytics products. REQUIRED QUALIFICATIONS, CAPABILITIES, AND SKILLS * Hold a Master’s degree in IT, Computer Science, MIS, Operations Research, or related field plus 3 years of relevant experience, or hold a Bachelor’s degree in the same fields plus 5 years of relevant experience. * Demonstrate advanced SQL capability, including complex joins, performance tuning, and incremental logic. * Apply strong data modeling expertise across grains, facts/dimensions, conformed dimensions, SCDs, and metric design. * Build or operate a semantic layer or metrics framework to standardize KPI logic and definitions. * Model semi-structured data (e.g., JSON) and integrate NoSQL sources for analytics use cases. * Use Snowflake and/or Databricks effectively in an analytics engineering context and apply practical Python for workflow automation and validation. * Practice strong stakeholder partnership and documentation discipline to drive clarity, correctness, and measurable outcomes. PREFERRED QUALIFICATIONS, CAPABILITIES, AND SKILLS * Leverage experience with testing and documentation frameworks for analytics engineering. * Apply familiarity with BI consumption patterns and tooling concepts (e.g., Tableau, Sigma, Looker). * Utilize orchestration tooling knowledge (e.g., Airflow, Dagster, ADF) with an SLA and reliability mindset. * Implement observability practices such as logging, alerting, and operational runbooks for data products. * Optimize cost and performance trade-offs through pragmatic platform tuning and design decisions. JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

Responsibilities

The role involves building analytics-ready data models and a trusted semantic layer to standardize business metrics. You will translate stakeholder needs into governed datasets and implement data quality and performance best practices in Snowflake and Databricks.