[Hiring] Engineering Manager @Naveera Technology LLC

Role Description

We are looking for an experienced Engineering Manager with strong hands-on expertise in AWS and GCP Data Engineering to lead a large-scale AWS-to-GCP data platform migration. The ideal candidate will have strong experience designing enterprise data platforms on AWS and migrating them to Google Cloud Platform (GCP). The role requires a combination of technical architecture, hands-on engineering, migration leadership, team management, and stakeholder management.

The candidate should have strong hands-on experience with AWS services such as S3, Glue, Redshift, Athena, Step Functions, and AWS DMS, along with strong GCP expertise across BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer.

The Engineering Manager will work closely with US-based stakeholders, architects, engineers, DevOps teams, Data Science, and BI teams to define the migration strategy and ensure successful execution.

Qualifications

• 15+ years of experience in Data Engineering, Data Architecture, Cloud Engineering, AI/ML Engineering, or related technology leadership roles.
• Strong hands-on experience with AWS Data Engineering and Data Architecture.
• 5+ years of strong hands-on GCP Data Engineering experience.
• Proven experience delivering AWS-to-GCP migration projects.
• Strong experience designing enterprise Data Lake and Lakehouse platforms on GCP.
• Strong hands-on experience with BigQuery, Google Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, Dataproc, IAM, and Terraform.
• Experience migrating AWS data workloads, pipelines, and platforms to GCP.
• Strong knowledge of AWS and GCP service mapping, migration patterns, modernization strategies, and cloud architecture best practices.
• Experience designing, building, and deploying AI/ML solutions on GCP using Vertex AI.
• Hands-on experience with Generative AI, LLM-based applications, RAG architectures, embeddings, vector search, prompt engineering, and enterprise AI assistants.
• Strong understanding of MLOps, including model training, model registry, CI/CD/CT, model deployment, monitoring, retraining, governance, and rollback strategies.
• Experience implementing secure and responsible AI solutions, including data privacy, model evaluation, access controls, auditability, and governance.
• Expert-level SQL and strong Python and PySpark skills.
• Strong data modeling, data warehousing, batch processing, and real-time data engineering experience.
• Experience managing and mentoring data engineering and cross-functional technical teams.
• Strong communication skills with experience working with US-based stakeholders.

Requirements

• AWS – Strong Existing Platform Experience
• Amazon S3
• AWS Glue
• AWS Glue Data Quality
• Amazon Redshift / Redshift Serverless
• Amazon Athena
• AWS Step Functions
• AWS DMS
• AWS Lake Formation
• IAM
• GCP – Target Platform
• BigQuery
• Google Cloud Storage
• Pub/Sub
• Dataflow / Apache Beam
• Cloud Composer / Airflow
• Dataproc / Spark
• Cloud Monitoring
• Cloud Logging
• Dataplex / Data Catalog
• Data Engineering
• Advanced Python
• Expert-level SQL
• Strong PySpark / Apache Spark
• ETL/ELT
• CDC
• Batch and streaming data processing
• Event-driven architecture
• Data pipeline optimization
• Data Architecture
• Enterprise Data Lake / Lakehouse
• Medallion Architecture
• Data Modeling
• Dimensional Modeling
• Multi-tenant Data Modeling
• Schema-on-Read / Schema-on-Write
• Data Lineage
• Metadata Management
• Data Governance
• Modern Data Stack
• dbt
• Apache Airflow
• Terraform
• Git / GitHub
• Cloud Build
• CI/CD
• Data Quality Frameworks
• OpenLineage is a plus

Benefits

• Lead large-scale AWS-to-GCP cloud transformation initiatives.
• Work on enterprise Data Lakehouse and analytics modernization projects.
• Flexible remote work environment.
• Exposure to global enterprise customers.
• Collaborative, innovation-driven engineering culture.
• Continuous learning and certification opportunities.