Hi,
I hope you are doing well.
Please find the job details below:
Job Title: Data Engineer
Must Have Qualifications:
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.
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
Schedule: Standard
Position Overview
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.
Responsibilities
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.
Preferred Skills
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.