Description

Key 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 data architects, business analysts, governance teams, and application teams to support enterprise data initiatives.

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

•                    Support cloud migration and modernization efforts 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 within financial services environments.

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

Required Skills & Experience:

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

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

•                    Experience working with modern cloud-based data platforms and data ecosystems.

•                    Hands-on expertise with Strong SQL expertise along with programming/scripting experience in Python, PySpark, or Snowpark.

•                    Experience with dbt (Data Build Tool) for:

·               Data transformation and modeling

·               ELT pipeline development within Snowflake/Databricks

·               Modular, reusable SQL-based data workflows

·               Data testing, documentation, and version control integration

•                    Experience with cloud platforms such as Azure, AWS, or GCP, including integration with Snowflake and Databricks.

•                    Solid understanding of data lake, data warehouse, and lakehouse architectures, and their implementation across platforms.

•                    Experience with orchestration and workflow tools (e.g., Airflow, Databricks Workflows, Snowflake Tasks) for pipeline scheduling and automation.

•                    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 diverse data sources, including:

·               APIs and microservices

·               File-based ingestion (batch)

·               Real-time/streaming data (e.g., Kafka, Spark Streaming)

•                    Knowledge of performance tuning, cost optimization, and scalability techniques across both Spark-based and Snowflake environments.

•                    Understanding of enterprise security, compliance, and governance standards, including RBAC, data masking, and encryption.

•                    Experience working in Agile and DevOps environments, including CI/CD for data pipelines.

Preferred Qualifications:

•                    Financial Services or Banking industry experience preferred.

•                    Experience supporting regulatory, risk, compliance, or operational reporting data 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 skills.

Education:

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field

Key Skills

Education

Bachelor's degree