
Senior Cloud Data Solution Engineer
6 days ago
We are seeking a highly skilled Senior Cloud Data Solution Engineer to design, develop, and optimize cloud-based data solutions that enable scalable, secure, and high-performance data platforms.
The role involves working across data engineering, cloud architecture, and solution design to deliver reliable pipelines, data lakes, and analytics solutions.
The ideal candidate should have deep expertise in cloud platforms (AWS, Azure, or GCP), modern data architectures, and big data technologies, along with strong problem-solving and leadership abilities.
Key Responsibilities :
Solution Design & Architecture :
- Architect and implement cloud-native data solutions (data lakes, data warehouses, lakehouses).
- Define data ingestion, storage, transformation, and access patterns for structured and unstructured data.
- Ensure scalability, performance, and cost optimization of cloud-based data solutions.
- Work closely with business stakeholders and solution architects to translate requirements into technical solutions.
Data Engineering & Development :
- Design and build data pipelines (ETL/ELT) using tools like Azure Data Factory, AWS Glue, GCP Dataflow, or Apache Airflow.
- Implement real-time and batch data ingestion from diverse sources (APIs, streaming, IoT, on-premise systems).
- Develop and maintain data models, schemas, and transformations to support analytics and AI/ML workloads.
- Work with SQL/NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra, DynamoDB, etc.
- Optimize storage and query performance in data warehouses (Snowflake, BigQuery, Redshift, Synapse).
Cloud & DevOps Integration :
- Deploy and manage data services on AWS, Azure, or GCP.
- Integrate security, governance, and compliance frameworks into data solutions.
- Build and maintain CI/CD pipelines for data infrastructure deployment.
- Implement observability, monitoring, and automated recovery for cloud data systems.
Collaboration & Leadership :
- Collaborate with data scientists, analysts, product managers, and application teams to enable data-driven solutions.
- Mentor junior engineers, share best practices, and drive engineering excellence.
- Participate in Agile ceremonies and contribute to sprint planning and technical roadmaps.
Required Skills & Qualifications :
- Bachelors or Masters degree in Computer Science, Engineering, or related field.
- 7+ years of experience in Data Engineering, with at least 3+ years in a cloud-native environment.
- Strong expertise in one or more cloud platforms (AWS, Azure, GCP) with hands-on experience in native data services.
- Proficiency in SQL, Python, and/or Scala for data engineering tasks.
- Experience with big data frameworks (Apache Spark, Hadoop, Databricks).
- Strong understanding of data modeling, metadata management, and data governance.
- Experience with ETL/ELT pipelines and workflow orchestration (Airflow, dbt, Talend, etc.
- Familiarity with API integrations, event streaming (Kafka, Kinesis, Pub/Sub).
- Excellent problem-solving, analytical, and communication skills.
(ref:hirist.tech)-
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