Data Analyst - Data Integration & Enablement

We are looking for a Data Analyst - Data Integration & Enablement to help build and strengthen the trusted data foundation that powers financial reporting, regulatory compliance, enterprise analytics, and data-driven decision making. You will work at the intersection of business, technology, and data, partnering with stakeholders across the organization to transform complex data into actionable insights and reliable enterprise assets.

In this role, you will leverage SQL, Python, and modern data platforms to analyze, integrate, validate, and govern data across enterprise systems. You will contribute to data modernization initiatives and gain exposure to cutting-edge technologies including Databricks, DBT, Google Cloud Platform (Google Cloud Platform), Data Mesh architectures, and AI/GenAI-enabled solutions.

What You’ll Do

• Partner with business and technology stakeholders to understand business objectives and translate them into data integration, reporting, and analytics requirements.
• Analyze, profile, and assess source systems using SQL and Python to identify data relationships, quality issues, anomalies, and integration opportunities.
• Define and document source-to-target mappings, transformation logic, metadata, business rules, and data lineage.
• Support enterprise data initiatives involving Data Warehouses, Data Lakes, Data Mesh environments, and Operational Data Stores (ODS).
• Develop and execute data validation, reconciliation, testing, and quality assurance processes to ensure accuracy and consistency of enterprise data.
• Build and enhance automated solutions for data profiling, validation, reconciliation, and reporting.
• Collaborate with data engineers, architects, analysts, and business teams to troubleshoot data issues and perform root cause analysis.
• Support data governance, transparency, and regulatory compliance through effective documentation and lineage management.
• Contribute to data modernization programs utilizing technologies such as DBT, Databricks, Google Cloud Platform, AI, and GenAI.
• Promote best practices in data quality, documentation, and continuous improvement across the organization.

• Bachelor’s degree in data Analytics, Computer Science, Information Systems, Business, or a related field.
• 2+ years of experience in Data Analysis, Data Integration, Business Intelligence, Data Engineering, or related discipline.

• Strong SQL skills, including:

• Complex queries
• Joins and aggregations
• Data profiling
• Data validation
• Data reconciliation
• Transformation analysis

Proficiency in Python for data analysis, automation, and data quality initiatives.

Experience documenting:

• Source-to-target mappings
• Transformation logic
• Metadata
• Data lineage
• Business rules

Understanding of ETL/ELT processes, data integration methodologies, and enterprise data environments.

Strong analytical, troubleshooting, and problem-solving skills.

Excellent stakeholder management, communication, and requirements-gathering abilities.

Ability to work effectively in cross-functional teams consisting of business and technical stakeholders. Preferred Qualifications

• Experience with Databricks.
• Exposure to dbt (Data Build Tool).
• Familiarity with Google Cloud Platform (Google Cloud Platform).
• Experience working with Enterprise Data Warehouses, Data Lakes, Data Mesh architectures, and Operational Data Stores (ODS).
• Knowledge of data governance, regulatory reporting, and data quality frameworks.
• Exposure to AI and GenAI use cases within data and analytics ecosystems.
• Experience supporting large-scale enterprise data transformation initiatives., * A curious and data-driven professional who enjoys solving complex business problems through data.
• Strong attention to detail and a passion for data quality and accuracy.
• Ability to bridge the gap between business needs and technical solutions.
• A collaborative team player who thrives in a fast-paced, enterprise environment.
• A continuous learner interested in modern data platforms and emerging technologies.