GCP Data Engineer( GCP MUST )

About Company

Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters .

GCP Data Engineer

Location- Dallas, TX Onsite Face to face interview

Rate : $60-$65/Hr on C2C  

JD

Mandatory Skills

GCP BigQuery
Apache Kafka
Dataflow / Apache Beam
Apache Spark / PySpark / Scala Spark
Vertex AI
Cloud Storage
Adobe Analytics
Python, Java, or Node.js
 

Required Qualifications

7–9 years of hands-on data engineering or ML data engineering experience in a production GCP environment.
Strong proficiency in Python, Java, or Node.js for pipeline development, feature-engineering scripts, and automation.
Hands-on experience with BigQuery, including partitioning, clustering, cost management, complex SQL, and ML-optimized table design.
Proficiency with Apache Kafka for real-time streaming ingestion.
Experience with Dataflow / Apache Beam for both streaming and batch pipelines.
Proficiency with Apache Spark, PySpark, or Scala Spark; Data Spark experience is a strong plus.
Solid familiarity with the GCP ecosystem, including Cloud Storage, Pub/Sub, Dataproc, and Cloud Composer / Airflow.
Experience building ML training pipelines and feature stores, preferably GCP Feature Store, with an understanding of the ML lifecycle, including feature engineering, data versioning, and train/evaluation splits.
Experience with Vertex AI Pipelines or similar MLOps tooling.
Demonstrated experience designing disaster recovery zones and failover strategies for cloud data platforms, including cross-region replication, RTO/RPO definition, and DR testing.
Experience with data archival design, including BigQuery table lifecycle management, Cloud Storage tiered storage policies, and long-term retention for regulated datasets.
Hands-on experience handling PHI under HIPAA, including field-level encryption and masking, de-identification techniques, audit logging, access-control policies, and HIPAA Security Rule compliance for data at rest and in transit.
Strong SQL and data-modeling skills, with experience in layered data lake or lakehouse architecture.
Nice to Have

Experience integrating Adobe Analytics data streams or Adobe Experience Platform.
Familiarity with Looker or Vertex AI as downstream consumers.
Knowledge of ClickThru file formats and external table patterns in BigQuery.
Experience with GCP CMEK customer-managed encryption keys for PHI dataset protection.
Familiarity with HIPAA BAA requirements in cloud vendor agreements.
Familiarity with NIST or HITRUST frameworks as applied to ML data pipelines.
Background in healthcare data, including Rx, clinical, or benefits domains.
Skills Summary

Mandatory Skills: Apache Spark, GCP Vertex AI, machine learning algorithms, Vertex AI, BigQuery, Kafka, Dataflow, Cloud Storage, Adobe Analytics, Python, Java, and Node.js.

Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment.