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PNC · 4 months ago

Data Engineer Senior - Data Products Organization (Hadoop, Spark 3, Python, Kafka)

Dallas Innovation Center - Luna Rd (TX270)

Full-time

Onsite

Mid, Senior Level

$65K/yr - $150K/yr

5+ years exp

PNC is a leading financial services institution that values its people as its greatest differentiator. The Data Engineer Senior will develop and implement data solutions across multiple applications, ensuring scalability and security while consulting on data migration and transformation processes.

BankingFinanceFinancial Services

No H1B

Responsibilities

Act as an internal consultant for other data engineering and technical teams to enhance and optimize the quality of their code, ensuring adherence to engineering best practices

Proven data literacy skills to describe business outcomes, data uses, data sources, and their management concepts and analytical approaches to all organizational levels in both business and technology

Demonstrate initiative to develop approaches to solutions as part of a team

Review architecture and identify areas for automation, optimization, right-sizing, and cost reduction to support health of the environment

Design, build and test data integration processes between business-critical applications to solve complex problems within financial services

Define and implement internal process improvements through the development of detailed analytics that provide actionable insights into key business performance metrics

Leads in developing, supporting and implementing data solutions for multiple applications in order to meet business objectives and user requirements

Leverages technical knowledge and industry experience to design, build and maintain technology solutions

Leads data requirement analysis and the data preparation process development for targeted data solutions

Leads in designing and building data service infrastructure on multiple data platforms, according the workflow

Oversees the development and implementation of data solutions for multiple applications to ensure its scalability, availability and maintainability

Consults on data migration and transformation to ensure the accuracy and security of data solutions

Qualification

HadoopSparkPythonKafkaSQLContainerizationPublic cloud platformsData AnalyticsData MiningData ScienceMachine LearningAnalytical ThinkingData AnalysisData ArchitectureDatabase StructuresProblem Solving

Required

Extensive experience with data technologies and distributed computing tools (Hadoop, Spark, Hive Kafka, HDFS, Sqoop, Impala, Beeline, CA7 Orchestration)

Lead experience as a Data Engineer

Strong proficiency in relevant programming languages such as Python, PySpark, Spark, SQL

Practical development and application of Kafka streaming and complex orchestration

Proficient in Containerization (OpenShift, Kubernetes, Docker, etc.)

Experience with public cloud platforms (prefer AWS and Microsoft Azure)

Knowledge of Linux

Knowledge of Iceburg

Roles at this level typically require a university / college degree, with 5+ years of industry-relevant experience

Specific certifications are often required

In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered

Bachelors