About the Role
About the Role
We are seeking a highly skilled Senior Data Engineer with deep expertise in Azure Cloud, Databricks, Azure Data Factory, Microsoft Fabric, Apache Spark, and Python to join our growing data team. The ideal candidate will be experienced in designing and implementing robust, scalable, and high-performance data solutions, with hands-on knowledge of cloud-native data architectures, modern big data frameworks, and distributed systems.
Key Responsibilities
Design, develop, and maintain end-to-end scalable data pipelines to ingest, process, and transform large-scale datasets across cloud and on-premise environments.
Build and optimize data lake / big data solutions using Azure Data Lake Storage Gen2, Azure Databricks, Azure Data Factory, Apache Spark, and related Azure services.
Develop high-performance Spark applications and optimize distributed data processing workloads.
Leverage programming expertise (primarily Python, with optional Scala/Java) for ETL/ELT pipelines, data transformations, and automation tasks.
Implement streaming data pipelines leveraging tools such as Kafka, Spark Structured Streaming, Flink, or Azure EventHub.
Work with NoSQL databases (Cosmos DB, Cassandra, MongoDB, etc.) and SQL-based data warehouses to enable analytics and reporting use cases.
Ensure performance optimization, cost efficiency, and scalability of big data workloads.
Apply DevOps and Infrastructure-as-Code (IaC) best practices for automated deployment and monitoring of data solutions (Azure DevOps, Terraform, Jenkins, GitHub Actions, etc.).
Collaborate with cross-functional teams (data scientists, analysts, product managers) to translate business requirements into scalable technical solutions.
Maintain high standards of data security, governance, and compliance within cloud environments.
Requirements
Required Qualifications
5+ years of industry experience in data engineering, software development, or related fields.
Proven track record in designing, building, and maintaining large-scale, cloud-based data solutions.
Strong expertise with Azure Data Services: ADLS Gen2, Azure Databricks, ADF, Azure Functions, Synapse Analytics (serverless & dedicated), Stream Analytics, Azure Data Explorer.
Proficiency in big data technologies such as Spark, Hive, Presto, HDFS, or equivalent.
Hands-on programming experience with Python and at least one additional language (Scala, Java, C#, etc.).
Strong experience with programming and building data solutions end to end in Spark.
Strong SQL skills, with ability to write, optimize, and tune complex queries.
Experience with real-time data streaming frameworks (Kafka, EventHub, Flink, Spark Streaming).
Familiarity with cloud networking, security, and performance optimization.
Experience applying CI/CD, DevOps, and IaC practices in data engineering projects.
Nice-to-Have Skills
Exposure to modern cloud-native platforms: Kubernetes, Docker, ArgoCD.
Knowledge of observability practices (logging, monitoring, tracing).
Experience with cloud security best practices.
Contributions to open-source projects related to data, cloud, or big data ecosystems.
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.