Cloud Data Engineer

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 CICD integration with GitHub Actions or similar.

Streaming Data Engineering -------------------------

Kafka Design and operate Kafka-based streaming pipelines. KafkaMSK Build producers and consumers using Python or JVM languages. Implement patterns such as topic partitioning, compaction, schema registry, and event versioning.

Data Modeling -------------

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 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.