Data Engineer

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I hope you are doing well.

Please find the job details below:

Job Title: Data Engineer

• Strong hands-on experience in Data Engineering and enterprise-scale data integration.

• Proven experience developing scalable ETL/ELT pipelines and distributed data processing solutions.

• Strong SQL expertise with programming experience in Python PySpark or Snowpark.

• Experience with dbt (Data Build Tool) for data transformation modeling ELT pipeline development testing documentation and version control.

• Hands-on experience with Snowflake Databricks Azure AWS or GCP.

• Strong understanding of data lake data warehouse and lakehouse architectures.

• Experience with orchestration tools such as Airflow Databricks Workflows or Snowflake Tasks.

• Experience supporting Master Data Management (MDM) and enterprise data governance initiatives.

• Familiarity with metadata management data lineage data cataloging and data quality processes.

• Experience integrating APIs batch file ingestion and real-time streaming technologies such as Kafka or Spark Streaming.

• Knowledge of enterprise security governance RBAC encryption and data masking.

• Experience working in Agile and DevOps environments with CI/CD pipelines.

• Bachelors degree in Computer Science Information Systems Engineering or a related field.

Schedule: Standard

We are seeking a hands-on Data Engineer with strong experience building scalable enterprise data solutions within Financial Services environments. The ideal candidate will have expertise in cloud-based data platforms modern data engineering practices enterprise data integration and Master Data Management (MDM). This role will support operational analytical and regulatory data initiatives while delivering secure reliable and scalable data solutions.

• Design develop and support scalable data pipelines and enterprise data integration solutions.

• Build and maintain batch and real-time data ingestion transformation and processing frameworks.

• Develop cloud-native data engineering solutions supporting enterprise data lake warehouse and lakehouse platforms.

• Implement ETL/ELT processes for structured semi-structured and unstructured data sources.

• Support Master Data Management (MDM) initiatives across security account client and reference data domains.

• Collaborate with architects business analysts governance teams and application teams to deliver enterprise data solutions.

• Implement data quality validation monitoring metadata management and data lineage processes.

• Support cloud migration and modernization initiatives involving legacy and enterprise data platforms.

• Optimize data processing storage and pipeline performance for scalability and operational efficiency.

• Ensure compliance with enterprise security governance and regulatory standards.

• Support reporting analytics and downstream data consumption through reliable data delivery.

• Financial Services or Banking industry experience.

• Experience supporting regulatory risk compliance or operational reporting environments.

• Exposure to real-time data processing and streaming technologies.

• Familiarity with CI/CD processes and infrastructure automation.

• Strong analytical troubleshooting and problem-solving skills.

• Excellent communication and collaboration abilities.