Key Responsibilities

- Design, develop, and maintain scalable data platforms and pipelines on Google Cloud Platform (GCP).
- Build batch and real-time data ingestion and processing solutions using Dataflow, Dataproc, Datastream, Pub/Sub, Composer, BigQuery,

and related GCP services.

- Design and implement data warehouse solutions and dimensional data models.
- Develop ETL/ELT pipelines and optimize data processing performance.
- Build and maintain APIs and data integrations using REST APIs,

webhooks, and Apigee.

- Implement infrastructure automation using Terraform and CI/CD best practices.
- Ensure data quality, monitoring, logging, alerting, and operational reliability of data pipelines.
- Implement security, governance, IAM controls, data masking, and

Cloud DLP standards.

- Collaborate with business stakeholders, analysts, data scientists,

and engineering teams to deliver data solutions.

- Contribute to AI/GenAI and conversational AI initiatives leveraging

GCP services.

Good to Have (Preferred Skills)

- Strong experience with RDBMS, advanced SQL, query optimization, and performance tuning.
- Experience with dimensional modeling, data warehousing, and ETL/ELT design patterns.
- Hands-on experience with GCP services including Dataproc, Dataflow,

Datastream, Pub/Sub, Composer, BigQuery,



and Spanner.

- Proficiency in Python, Java, or Scala.
- Experience with batch and streaming architectures, CDC, and real-time data replication.
- Hands-on experience with dbt/Dataform and data storage formats such as Parquet and Avro.
- Experience with data observability, monitoring, lineage, and data quality frameworks.
- Experience with CI/CD, Terraform, Infrastructure as Code, and

Git-based development.

- Experience implementing automated testing for data pipelines.
- Understanding of SRE principles, SLAs/SLOs, and resilient pipeline design.
- Familiarity with AI-assisted development tools and LLM coding assistants.
- Knowledge of data governance, security, and cloud cost optimization.
- Solid communication, stakeholder management, and collaboration skills.

Nice to Have (Optional Skills)

- Experience with Knowledge Graphs.
- Experience with NoSQL databases such as Bigtable and Firestore.
- Experience supporting ML and analytics workloads, feature engineering pipelines, and Looker.
- GCP Professional Data Engineer Certification.
- PMP Certification and Agile delivery experience.
- Exposure to GenAI solutions such as Gemini, RAG, CCAI, or

Dialogflow CX.

📌 Cloud Data Engineer(GCP) (Bengaluru)
🏢 BCE Global Tech
📍 Bengaluru