Senior Data Streaming Engineer

Bank of America

. Drive efforts to develop and deliver complex data solutions for technology and business goals .

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

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and delivering complex data solutions, with a strong focus on real-time data pipelines and data lakehouse architectures. Proficient in data integration, transformation, and ensuring data quality across various systems.

Highest-signal resume keywords

Apache FlinkConfluent KafkaApache IcebergPythonAdvanced SQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData WarehousingEvent-Driven ArchitecturesData ModelingStreaming ArchitecturesKafka-Based IngestionReal-Time AnalyticsCI/CD PracticesData Quality AssuranceData Governance

Soft Skills

MentoringCollaborationTechnical Issue ResolutionStakeholder LiaisonStory Refinement

Tools & Technologies

AWSAzureGCPJiraBitbucketSparkHiveHDFSKafka ConnectKsqlDB

Industry Keywords

Data LakesMDM SystemsData IntegrationStreaming Data FrameworkData LineageMetadata ManagementBatch SystemsHybrid EnvironmentsInfrastructure AutomationOffice-Based Attendance

Tech Stack

Tools & technologies

ApacheAWSAzureGoogle Cloud PlatformHDFSITSMJavaKafkaOraclePySparkPythonRDBMSScalaSDLCServiceNowSparkSQL

About the role

Key responsibilities & impact

Drive efforts to develop and deliver complex data solutions for technology and business goals
Lead code design and delivery involving data integration, cleaning, transformation, and control
Design and implement real-time data pipelines using Apache Flink and Confluent Kafka
Transform legacy batch and RDBMS-based workflows into event-driven streaming architectures
Build and optimize streaming ingestion, transformation, and enrichment pipelines
Develop and maintain Apache Iceberg-based data lakehouse tables
Ensure data quality, reconciliation, and consistency across streaming and batch systems
Optimize streaming jobs, including 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 framework best practices
Support CI/CD, deployment, and operational monitoring of streaming pipelines
Lead story refinement, requirements delivery, testing, triage, documentation, and technical issue resolution
Lead complex IT projects and define data pipelines for data-informed decision making
Mentor Data Engineers and monitor key performance indicators and internal controls
Liaise with vendors, stakeholders, Product teams, and Software Engineering teams

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
Experience with real-time analytics use cases
Experience with Kafka Connect, ksqlDB, or stream enrichment frameworks
Familiarity with data governance, lineage, and metadata management
Experience with AWS, Azure, or GCP
Exposure to DevOps and infrastructure automation
Experience with Jira and Bitbucket
Must work in an in-office culture with office-based attendance requirements

Benefits

Comp & perks

Discretionary incentive eligible
Eligible to participate in the annual discretionary plan
Industry-leading benefits
Paid time off
Resources and support for employees
40 hours per week
In-office culture with role-specific flexibility