JPMorgan is hiring for the position of Associate – Analytics Data Engineer in Bengaluru, India. Candidates with a Bachelor’s/ Master’s degree are eligible to apply for this position. The complete information, eligibility criteria, and requirements are provided below.
Job Description:
| Company Name | JPMorgan Chase & Co. |
| Position | Associate – Analytics Data Engineer |
| Qualifications | Bachelor’s/ Master’s Degree |
| Experience | Experienced |
| Location | Bengaluru, India |
Key Responsibilities:
- Lead the development of analytics data models, including dimensional and domain-oriented models, optimized for reporting, business intelligence, and self-service data consumption.
- Design and maintain a semantic layer with standardized metrics, dimensions, entities, and business definitions to ensure consistency across dashboards and analytical reports.
- Translate stakeholder requirements into clear data modeling deliverables, including entity definitions, data granularity, metric specifications, and acceptance criteria.
- Develop and maintain data transformations primarily using SQL, leveraging Python for complex logic, automation, and data validation when required.
- Implement and promote data quality controls, including automated tests, reconciliations, and anomaly detection, to ensure the accuracy and reliability of business-critical metrics.
- Optimize data model performance in Snowflake and/or Databricks by implementing efficient joins, partitioning and clustering strategies where applicable, and balancing cost and performance.
- Collaborate with upstream data teams to understand source systems, including semi-structured data and non-relational sources, and ensure analytics models accurately represent business requirements.
- Establish and maintain data modeling standards, including naming conventions, documentation, data lineage, metric governance, and change management for semantic definitions.
- Support data enablement by documenting curated datasets, developing user guidance, and helping data consumers effectively adopt and use the semantic layer.
Eligibility Criteria:
- A Master’s degree in Information Technology, Computer Science, Management Information Systems, Operations Research, or a related field, along with at least 3 years of experience in the offered role, as an Analytics Engineer, or in a related occupation.
- Alternatively, a Bachelor’s degree in Information Technology, Computer Science, Management Information Systems, Operations Research, or a related field, along with at least 5 years of experience in the offered role, as an Analytics Engineer, or in a related occupation.
- Advanced proficiency in SQL, including complex joins, performance tuning, and incremental data processing logic.
- Strong understanding of data modeling concepts, including fact and dimension tables, data granularity, conformed dimensions, slowly changing dimensions, and metric design.
- Demonstrated experience in building or managing a semantic layer or metrics framework, with the ability to standardize key performance indicator (KPI) logic and business definitions across analytical systems.
- Experience working with semi-structured data, such as JSON, and non-relational data sources, including modeling them for analytical purposes.
- Knowledge of data governance concepts, including role-based access control, data classification, data lineage, and audit requirements.
- Hands-on experience working with Snowflake and/or Databricks in an analytics environment.
- Practical proficiency in Python for data workflows, including validation, automation, and the development of notebooks and scripts.
- Ability to collaborate with stakeholders, clarify ambiguous requirements, and deliver measurable business outcomes.
- Strong documentation skills and attention to data accuracy, consistency, and reliability.
Preferred Skills:
- Experience with data testing methodologies and technical documentation.
- Familiarity with business intelligence tools and semantic data consumption practices, such as Tableau, Sigma, or Looker.
- Knowledge of data orchestration and observability tools, such as Airflow, Dagster, or Azure Data Factory, including logging, alerting, and service-level agreement (SLA) management.
About Company:
JPMorgan Chase & Co., 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.
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