Position Summary
We are seeking a Senior Data Engineer with specialized expertise in data streaming technologies to join our data team. This role focuses on building and maintaining high-performance data streaming architectures that enable real-time data processing and analytics. The ideal candidate will have deep experience with Apache Kafka, AWS Managed Streaming for Apache Kafka (MSK), Amazon Kinesis, and related streaming technologies in cloud environments.
Role Focus
A Senior Data Engineer at Effectual is primarily responsible for building and maintaining the streaming data architecture that enables real-time data processing and analytics. This involves constructing robust data streaming pipelines that transform and transport data from various sources in real-time, ensuring data flows efficiently through streaming systems for immediate analysis and operational decision-making. You will focus on the efficient and secure management of streaming data systems, ensuring that data is processed, stored, and made available for real-time analytics and downstream applications.
Essential Duties and Responsibilities
Streaming Data Architecture & Pipeline Development
Design, build, and maintain scalable streaming data architectures using Kafka, MSK, and Kinesis
Develop real-time data pipelines that handle high-volume, high-velocity data streams
Implement event-driven architectures and microservices patterns for streaming data processing
Create and optimize data streaming topologies for complex event processing scenarios
Design fault-tolerant streaming systems with proper error handling and data recovery mechanisms
Kafka & MSK Management
Configure, deploy, and manage Apache Kafka clusters and AWS MSK environments
Implement Kafka Connect pipelines for streaming data integration
Design optimal Kafka topic partitioning strategies and replication configurations
Monitor and optimize Kafka cluster performance, throughput, and latency
Implement Kafka security configurations including SSL/TLS, SASL, and ACLs
Manage Kafka Schema Registry for data serialization and evolution
Kinesis & AWS Streaming Services
Design and implement Amazon Kinesis Data Streams and Kinesis Data Firehose solutions
Configure Kinesis Analytics applications for real-time stream processing
Optimize Kinesis shard management and auto-scaling configurations
Implement Kinesis data retention and archival strategies
Integrate Kinesis with other AWS services for comprehensive streaming solutions
Data Processing & Analytics
Develop real-time stream processing applications using Apache Spark Streaming, Kafka Streams, or AWS Lambda
Implement complex event processing (CEP) patterns for real-time analytics
Build streaming ETL pipelines that transform data in motion
Create real-time aggregations, windowing operations, and stateful stream processing
Optimize streaming query performance and resource utilization
Integration & Data Flow Management
Ensure seamless integration between streaming systems and data lakes, data warehouses, and operational databases
Implement data lineage and monitoring for streaming data pipelines
Create automated data quality checks and validation for streaming data
Manage data serialization formats (Avro, JSON, Protobuf) and schema evolution
Coordinate with data scientists and analysts to ensure streaming data meets analytical requirements
DevOps & Infrastructure Management
Implement Infrastructure as Code (IaC) for streaming data platforms using Terraform or CloudFormation
Automate deployment and management of streaming infrastructure through CI/CD pipelines
Monitor streaming system health, performance metrics, and alerting
Implement disaster recovery and high availability strategies for streaming systems
Stay current with emerging trends in streaming technologies and cloud-native solutions
Team Collaboration and Project Management
Collaborate with data architects, data scientists, and application teams on streaming data requirements
Support rigorous project governance through daily progress reviews and time tracking
Provide technical leadership and mentorship to junior data engineers
Communicate complex streaming concepts to technical and non-technical stakeholders
Operate with transparency and responsiveness to support high-performing teams
Skills and Experience
Required Experience
7+ years of experience in the data engineering field with significant streaming data specialization
Bachelor's degree in Computer Science, Engineering, or related STEM field
Extensive hands-on experience with Apache Kafka including cluster management, performance tuning, and ecosystem tools
Proven experience with AWS MSK and Amazon Kinesis services in production environments
Strong background in real-time data processing and stream analytics
Technical Proficiencies
Streaming Technologies: Apache Kafka, Kafka Connect, Kafka Streams, Amazon MSK, Amazon Kinesis (Data Streams, Data Firehose, Analytics)
Programming Languages: Proficient in Python, Java, and Scala for streaming applications
Stream Processing Frameworks: Apache Spark Streaming, Apache Flink, AWS Lambda for stream processing
Data Serialization: Experience with Avro, Protocol Buffers, JSON, and schema registry management
Big Data Technologies: Hadoop ecosystem, Apache Spark, distributed computing concepts
Database Technologies: SQL and NoSQL databases, data warehousing solutions, time-series databases
Cloud and Infrastructure Skills
AWS Services: Deep knowledge of AWS streaming and analytics services (MSK, Kinesis, Lambda, EMR, Glue)
Containerization: Docker and Kubernetes for streaming application deployment
Infrastructure as Code: Terraform, CloudFormation for streaming infrastructure automation
Monitoring: CloudWatch, Prometheus, Grafana for streaming system observability
Security: Implementation of streaming data security, encryption, and access controls
Development and Operations Skills
Expert use of code versioning tools such as GitHub
Expert knowledge of Agile methodologies and delivery practices
Experience with CI/CD pipelines for streaming data applications
Understanding of data APIs, REST services, and microservices architectures
Leadership Competencies
Leadership & Team Management
Risk Management and mitigation strategies for streaming systems
Conflict Resolution
Strategic Planning & Leadership for data streaming initiatives
Resource Management and capacity planning
Change Management for streaming technology adoption
Target Certifications
Core AWS Certifications
AWS Data Engineer Associate (required)
AWS Solutions Architect Professional (preferred)
AWS Developer Professional (recommended)
Streaming-Specific Certifications
Confluent Certified Administrator for Apache Kafka (highly recommended)
Confluent Certified Developer for Apache Kafka (preferred)
Additional Valuable Certifications
AWS Big Data Specialty (if available in current form)
AWS Security Specialist
Certified Associate Data Analyst with Python
Certified Professional Python Programmer Level 1
Databricks Data Engineer Professional
Programming Certifications
Certified Associate Python Programmer
Java or Scala certification (Oracle Certified Professional)
Preferred Qualifications
Experience with Apache Flink for advanced stream processing
Knowledge of Apache Pulsar as an alternative messaging system
Experience with event sourcing and CQRS patterns
Understanding of Apache Airflow for batch and streaming workflow orchestration
Experience with ksqlDB for stream processing using SQL
Background in financial services, IoT, or other real-time data intensive industries
Experience with multi-cloud streaming architectures
Knowledge of Apache NiFi for data flow automation
Performance Metrics
Streaming pipeline uptime and reliability (99.9%+ availability)
Data processing latency and throughput optimization
Cost optimization of streaming infrastructure
Successful real-time analytics implementations
Team productivity and knowledge transfer effectiveness
Company Offered Benefits
Full-time employees are eligible to participate in our employee benefit programs:
Medical, dental, and vision health insurances,
Short term disability, long term disability and life insurances,
401k with Company match
Paid time off (PTO) (120 hours PTO that accrue over one year)
Paid time off for major holidays (14 days per year)
These and any other employee benefit offerings are subject to management’s discretion and may change at any time.
Physical Demands and Work Environment
The work is generally performed in an office environment. Physical demands include sitting, keyboarding, verbal communication, written communication. Employees are occasionally required to stand; walk; reach with hands and arms; climb or balance; and stoop, kneel, crouch, or crawl. The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this position. Reasonable accommodation may be made to enable individuals with disabilities to perform the functions.
Salary Range for this position: $150,000-$180,000
CA ID: IT10000478
"Salary ranges provided are for informational purposes only and may vary depending on factors such as experience, qualifications, and geographic location. The final salary offer will be determined based on the candidate's skills and alignment with the role requirements."
This job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described, and may be amended anytime at the sole discretion of the Employer. Duties and responsibilities are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the incumbents will possess the skills, aptitudes, and abilities to perform each duty proficiently. This document does not create an employment contract, implied or otherwise, other than an “at will” relationship. Effectual Inc. is an EEO employer and does not discriminate on the basis of any protected classification in its hiring, promoting, or any other job-related opportunity.