Senior Data Software Engineer @
3 days ago
- BS in Computer Science, Information Technology, Business / Management Information Systems or related field
- Experience in lieu of degree will be considered
- Typically minimum of 4 years of strong development background in ETL tools like GCP-Data Flow , PySpark , SSIS
- Experience in Google cloud platform - GCP Pub/Sub, Datastore, BigQuery, BigLake, AppEngine,
- Experience in a major cloud platform such as GCP, AWS, Azure is preferred
- Strong proficiency in languages such as Python, Java, Scala for data processing and pipeline development.
- Expertise in designing star schemas, snowflake schemas, and other dimensional models per Kimball methodology.
- SQL Proficiency: Deep understanding of SQL, query optimization, and performance tuning.
- Proficient in repo management, branching strategies, version control using GIT, VSTS and Teamforge, etc
- Experience with Big Data: Familiarity with big data technologies (e.g., Spark, Kafka, DBT, Iceberg, Parquet) is a plus.
- Strong analytical, planning, and organizational skills with an ability to manage competing demand
- Excellent communication skills, verbal and written; should be able to cross-functionally collaborate across business teams (stakeholders) and other technology groups as needed.
- Create diagrams using industry standards such as UML & C4 to create clear and concise documentation for knowledge transfer and communication duties. Diagram As Code experience with Mermaid or PlantUML is a plus.
- BS or Masters in Computer Science, Information Technology, Business / Management Information Systems, Quantitative Analytics, Statistics, Mathematics, Data Science, or related field
- Software Engineering: Payment Information Systems or any Technical degree
- Familiarity with OpenTelemetry
- Basics to advance level of AI/ML knowledge.
- Experience in NoSQL
- Exposure to the Payment / FinTech industry is a plus
- Skills / Knowledge - A seasoned, experienced professional with a full understanding of the area of specialization; resolves a wide range of issues in creative ways. This job is fully qualified, career-oriented, and a journey-level position.
- Job Complexity - Works on problems of diverse scope where analysis of data requires evaluation of identifiable factors. Demonstrates pragmatic judgment in selecting methods and techniques for obtaining solutions. Networks with senior internal and external personnel in their own area of expertise.
- Supervision - Normally receives little instruction on day-to-day work, general instructions on new assignments.
As a Senior Software Data Engineer, you will help in the design, implementation, and testing of our data pipelines, from extract to consumption; ensuring scalable, high-performance delivery into our GPN Data Lakehouse. Leveraging expertise in dimensional modeling and data engineering best practices, you will help in architecting data models, datawarehouse/datalake architecture, test data pipelines, optimize data pipelines, and maintain high standards for data quality, accuracy, and accessibility. As a senior engineer, there will be cross-functional collaboration, and mentorship to drive data-driven insights and empower business decision-making.
,[Data Architecture and Modeling: Design and implement robust data models, leveraging dimensional modeling principles to structure data for performance, usability, and scalability in reporting and analytics., Contribute in the development of efficient ETL processes, data pipelines, and workflows to transform, integrate, and load data from multiple sources into the data lake., Help solution and optimize data lake solutions that support high query performance and can scale with increasing data volume and complexity with appropriate industry standard KPIs. , Data Governance & Quality: Develop and enforce data quality standards, including validation, transformation, and cleansing rules to ensure data accuracy and consistency across the organization., Performance Tuning: Perform detailed performance tuning of ETL processes and query optimization to improve data processing speeds and reduce latency in data access., Develops a general understanding of TSYS/Global Payments, software platforms, and the credit card industry.] Requirements: Java, Python, BS, Degree, ETL, SSIS, GCP, PUB, PySpark, BigQuery, Cloud, sub, Snowflake, Cloud platform, big lake, AWS, app engine, Scala, Azure, SQL, Google cloud platform, Git, Performance tuning, vsts, teamforge, c4, Communication skills, Kafka, dbt, Big Data, UML, AI, iceberg, NoSQL, parquet, Spark, open telemetry, ML Additionally: Sport subscription, Private healthcare, International projects, Training budget, Lunch card.-
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