About the Role
About the Role
We are looking for a Cloud Data Engineer with hands-on experience in Azure, AWS, or other cloud platforms to design, build, and scale robust data pipelines and data lake architectures. This role requires deep technical expertise in Big Data technologies, data ingestion, real-time processing, and data transformation within a modern cloud environment.
You will work closely with data scientists, analysts, and software engineers to deliver high-quality, secure, and efficient data solutions that drive business insights and innovation.
Key Responsibilities
Design and develop data pipelines, ETL/ELT workflows, and data lake solutions on Azure, AWS, or similar cloud platforms.
Build scalable and secure data architectures supporting analytics, BI, and machine learning use cases.
Leverage cloud-native data services such as Azure Data Factory, Microsoft Fabric, Databricks, Synapse Analytics, or AWS Glue, EMR, Lake Formation, Athena.
Work with Big Data frameworks like Apache Spark, Flink, Hive, or Impala to process and analyze large-scale datasets.
Implement and manage real-time streaming solutions using Kafka, Azure Event Hub, AWS Kinesis, or GCP Pub/Sub.
Write optimized SQL queries for data transformation, aggregation, and performance tuning.
Apply DevOps and CI/CD practices to automate data pipelines and ensure reliable deployment processes.
Collaborate across teams to maintain data quality, security, and governance in all data engineering workflows.
Contribute to cloud infrastructure optimization, ensuring scalability, cost efficiency, and reliability.
Requirements
Required Skills and Qualifications
4+ years of experience in data engineering, software development, business intelligence, or data science.
Proven experience building and maintaining data lake and big data platforms on Azure or AWS.
Hands-on knowledge of key Azure/AWS Data Services, including:
Azure: Microsoft Fabric, ADLS Gen2, Azure Data Factory, Databricks, Synapse Serverless/Dedicated SQL Pool, Azure Functions, Stream Analytics, Data Explorer.
AWS: S3, Glue, EMR, Athena, Lake Formation, Lambda, Kinesis.
Strong understanding of Big Data technologies such as Apache Spark, Flink, Hive, Impala, HDFS, Dataproc, EMR, or BigQuery.
Experience with streaming and event-driven data pipelines (Kafka, Spark Streaming, Flink, EventHub, Pub/Sub, Confluent).
Proficient in SQL for data analysis, transformations, and troubleshooting.
Good grasp of cloud computing, networking, and security within Azure or AWS ecosystems.
Experience with DevOps, CI/CD, and Infrastructure-as-Code (IaC) tools in data analytics projects.
Proficiency in at least one programming language: Python, Scala, Java, Go, or Rust.
Nice-to-Have Skills
Strong desire to learn and implement distributed systems and cloud-native best practices.
Advanced programming skills in Python and/or Scala.
Familiarity with containerization and orchestration tools such as Docker, Kubernetes, and ArgoCD.
Understanding of cloud storage systems (Azure Data Lake Storage Gen2, GCS, S3).
Knowledge of observability and monitoring tools for logging, tracing, and performance optimization.
Exposure to CI/CD and automation tools such as Jenkins, GitHub Actions, ArgoCD, Terraform, Helm, Azure DevOps, or GCP Cloud Build.
Why Join Us
Work with cutting-edge cloud and data engineering technologies.
Collaborate with a passionate team of data experts, engineers, and architects.
Continuous opportunities for professional growth, certifications, and upskilling.
Be part of innovative projects leveraging modern cloud-native and big data architectures.
About the Company
EnablerMinds is a next-generation boutique company delivering end-to-end Cloud, Data & AI solutions. Our elite team of data engineers, architects, data scientists, AI engineers and industry specialists empowers enterprises to modernize their data ecosystems, accelerate AI adoption, and unlock transformative business value.
With proven methodologies, enterprise-ready frameworks, and an agile delivery and staffing model, we deliver high-performance, scalable, and cost-efficient outcomes tailored to the needs of tomorrow’s intelligent enterprise.
We welcome applicants of all genders, backgrounds and identities.