Senior Data Streaming Engineer

Bank of America

. Lead story refinement and deliver requirements through the delivery lifecycle .

Posted 9/15/2026full-timeJersey City • New Jersey • United StatesSenior💰 $104,000 - $157,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in data engineering, focusing on building and optimizing data pipelines, ensuring data quality, and implementing event-driven architectures. Proficient in leading complex technology projects and mentoring teams while adhering to best practices in data management and CI/CD processes.

Highest-signal resume keywords

Apache FlinkConfluent KafkaApache IcebergPythonAdvanced SQL

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData WarehousingData LakesEvent-Driven ArchitecturesData ModelingStreaming ArchitecturesSQL OptimizationData Quality ControlsData TransformationIntegration with Oracle

Soft Skills

LeadershipCollaborationMentoringCommunicationProblem-Solving

Tools & Technologies

CI/CDJiraBitbucketApache SparkHiveHDFSServiceNowKafka ConnectKsqlDBCloud Data Platforms

Industry Keywords

Data GovernanceMetadata ManagementStreaming Data Best PracticesData QualityData Informed Decision Making

Tech Stack

Tools & technologies

ApacheCloudHDFSITSMJavaKafkaOraclePySparkPythonRDBMSScalaSDLCServiceNowSparkSQL

About the role

Key responsibilities & impact

Lead story refinement and deliver requirements through the delivery lifecycle
Code complex solutions to integrate, clean, transform, and control data
Build data transformation processes, data structures, metadata, data quality controls, dependencies, and workload management
Assemble complex data sets and communicate deployment information
Document system requirements and collaborate with development teams on data requirements and feasibility
Lead testing teams, develop test plans, analyze test reports, identify issues, and lead triage
Close gaps in data management standards with technology partners and stakeholders
Lead complex technology projects, ensuring on-time delivery, release-process adherence, and risk management
Define and build data pipelines for data-informed decision making
Mentor Data Engineers and monitor key performance indicators and internal controls
Design and implement real-time pipelines using Apache Flink and Confluent Kafka
Transform legacy batch and RDBMS workflows into event-driven streaming architectures
Build and optimize streaming ingestion, transformation, and enrichment pipelines
Develop and maintain Apache Iceberg data lakehouse tables
Ensure data quality, reconciliation, and consistency across streaming and batch systems
Optimize streaming-job performance, state management, checkpointing, and scalability
Design partitioning, schema evolution, and storage strategies using Iceberg
Integrate data across systems including ITSM platforms such as ServiceNow
Collaborate with architecture and platform teams on streaming-data best practices
Support CI/CD, deployment, and operational monitoring of streaming pipelines

Requirements

What you’ll need

10+ years of IT experience with strong focus on data engineering
5+ years in data warehousing, data lakes, or MDM systems
Strong experience with Apache Flink, Confluent Kafka, and Apache Iceberg
Proficiency with Python, PySpark, or Java/Scala
Advanced SQL querying and optimization
Experience designing event-driven and streaming architectures
Deep understanding of data modeling for streaming and lakehouse systems
Experience with Kafka-based ingestion patterns and CDC frameworks
Knowledge of Parquet and Avro data formats and optimization techniques
Experience integrating with Oracle, DB2, and SQL Server and migrating to modern platforms
Familiarity with Spark, Hive, and HDFS in hybrid environments
Experience with SDLC practices, CI/CD pipelines, and version control
Ability to translate design into production-grade implementations
Desired: experience with real-time analytics, Kafka Connect, ksqlDB, stream enrichment frameworks, data governance, lineage, metadata management, cloud data platforms, DevOps, infrastructure automation, Jira, and Bitbucket

Benefits

Comp & perks

Discretionary incentive eligible; eligible to participate in the annual discretionary plan
Industry-leading benefits
Paid time off
Resources and support to employees
Opportunities to learn, grow, and make an impact
Inclusive workplace supporting teammates’ physical, emotional, and financial wellness
Recognition and rewards for performance