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