Cloud Data Engineer

RESPONSIBILITIES:
Kforce has a client in Boston, MA that is seeking a Cloud Data Engineer.


Lakehouse Architecture (Apache Iceberg):
* Design and build Iceberg-based data lakes with ACID-compliant, versioned datasets
* Implement Iceberg table evolution (schema evolution, partition spec, snapshot management)
* Develop best practices for Iceberg governance, metadata compaction, and performance tuning

Data Pipelines & Distributed Processing:
* Build scalable batch and streaming pipelines using AWS services (S3, EMR, Glue, Lambda, Step Functions)
* Develop ingestion and transformation workflows using Python, Spark, or Flink
* Implement CDC pipelines using Kafka Connect or equivalent tooling
* Ensure robust CI/CD integration with GitHub Actions or similar

Streaming Data Engineering (Kafka):
* Design and operate Kafka-based streaming pipelines (Kafka/MSK)
* Build producers/consumers using Python or JVM languages
* Implement patterns such as topic partitioning, compaction, schema registry, and event versioning

Data Modeling, Quality, and Observability:
* Design data models for analytical and operational use cases using Iceberg tables
* Implement automated data quality checks, validation rules, and anomaly detection
* Build lineage, monitoring, alerting, and pipeline observability

AWS Architecture & Operations:
* Apply best practices for AWS security, cost optimization, and data governance
* Manage IAM, KMS, S3 object lifecycle management, networking, and data encryption
* Operationalize EMR/Glue jobs, containerized workloads, or serverless workloads

Cross Functional Collaboration:
* Partner with analytics, platform, and product teams to deliver high-quality data products
* Participate in design reviews, architecture discussions, and roadmap planning
* Mentor junior engineers and contribute to engineering standards

REQUIREMENTS:
* 4-10+ years of experience in Data Engineering or similar roles
* Strong hands-on experience with Apache Iceberg (table design, evolution, metadata, partitioning)
* Deep experience with AWS data stack: S3, EMR, Lambda, Glue, IAM, Step Functions, CloudWatch
* Strong proficiency in Kafka (producers/consumers, schema registry, partitioning strategies)
* Fluency in Python for data pipelines, automation, and APIs
* Experience with distributed engines such as Spark, Flink, or PySpark
* Expertise in scalable ETL/ELT pipelines and real-time streaming architectures
* Strong SQL and data modeling expertise

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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