Data Engineer

Data engineers power the backbone of data-driven organizations by building robust systems that transform raw data into trusted insights - delivering a single, integrated view of enterprise data to support performance reporting, lead generation, and customer experience, while enabling smarter decisions through clean, timely, and accessible data, including ad hoc requests.

Responsibilities

Designs and Maintains Data Architecture

• Builds scalable and efficient data systems, including data lakes, warehouses, and pipelines, to support enterprise-wide data needs
• Designs, develops and generates datamarts, performance reports, dashboards, traditional leads and customized data extraction in line with business needs
• Interprets the users’ data requirements and execution of the approved business rules / data parameters
• Provides end-to-end support on the Enterprise Data Platform and data tools from gathering requirements, translating business requirements into detailed functional specifications, developing and managing the data life-cycle process
• Creates appropriate documentation that allows stakeholders to understand the steps of the data analysis process and duplicate or replicate the analysis if necessary
  
  

• Implements validation, monitoring, and cleansing processes to maintain accurate, consistent, and reliable data
• Conducts data quality / reasonableness testing on the datamarts and reports generated with applied business rules
  
  

• Creates ETL/ELT workflows to ingest, transform, and load data from various sources, ensuring performance and scalability
• Discusses with System Owners, Data Owners, Business Data Teams and Enterprise Data Integration Team for any system enhancements in the source application that will impact the data platforms by analyzing the revision / enhancement and conducting user acceptance testing
• Works with the IT Team to identify opportunities for process improvements that will include automation of manual process and identify opportunities for data acquisition
  
  

• Provides secure, timely access to data for analysts, scientists, and business users, while managing permissions and compliance
• Defines and updates data and report / dashboard access rights including folder restrictions
  
  

• Supports Bank’s initiative on projects based on defined activities by defining business requirements, conducting UATs, providing data extraction requirements, monitoring project timelines and reporting issues, if any
• Responds to custom data requests and deliver insights that support business growth, performance tracking, and customer experience initiatives
  
  

• Performs other Data Management or Data Platform-related tasks that may be assigned from time to time
  
  

• Must have a Bachelor’s Degree in Management, Economics, Business. Data Analytics or related courses
• Must have 3–5 years of experience in data engineering or related roles
• Must have knowledge and background in Data Architecture & Modeling
• Must understanding of relational and non-relational databases, data warehousing, and data lake design
• Must have knowledge and background in ETL/ELT Processes
• Must have deep knowledge of data ingestion, transformation, and loading techniques
• Must have knowledge and background in Big Data Technologies
• Must have Familiarity with tools like Apache Spark, Hadoop, Kafka
• Must have knowledge and background in Cloud Platforms
• Must have experience with AWS, Azure, or Google Cloud for data infrastructure
• Must have knowledge and background in Data Governance & Security
• Must have knowledge of data privacy, access control, and compliance standards
• Must have Programming proficiency in Python, SQL, and optionally Scala or Java
• Must have Data Pipeline Development skills in building and maintaining scalable, automated workflows
• Must have Tool Proficiency or experience in any of the following: Dbeaver, SAS, AWS Glue, Talend, Kafka, Airflow, dbt, Snowflake, Redshift, BigQuery, etc.
• Must have strong analytical skills to troubleshoot data issues and optimize performance
• Must have collaboration & communication skills and ability to work with cross-functional teams and translate technical concepts for non-technical stakeholders
• Must be knowledgeable in Data Management Tools such as SAS Data Flux, etc
• Must be knowledgeable in Database language such as SQL, SAS Base, SAS Base, OA, SAS Studio, Enterprise Guide, etc
• Must be knowledgeable in Data Visualization such as SAS Visual Analytics Tool