N-iX
mining
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at N-iX. Skills: Data pipelines, Azure Synapse, Databricks, Data infrastructure. Gather business requirements. Analyze business requirements”
Industry & Context.
Problem-solving
What They're Looking For.
Must Have
4+ years of experience in data engineering, analytical and communication skills, hands-on experience with Azure Data Factory, Solid experience with Azure Synapse Analytics, Proficiency in SQL, Proficiency in Python, Understanding of data security, problem-solving mindset, ability to work autonomously
Nice to Have
Proven experience with Databricks, Experience with Azure Purview, Knowledge of streaming data patterns, Familiarity with dbt, Power Platform awareness
What You'll Do.
Gather business requirements
Analyze business requirements
Design data pipelines
Maintain data pipelines
Orchestrate ingestion
Develop data transformation logic
Optimize analytical workloads
Build Databricks notebooks
Maintain Databricks jobs
Implement API extraction patterns
Handle authentication
Handle error recovery
Design lakehouse architecture
Maintain lakehouse architecture
Document data lineage
Collaborate with Analytics Engineers
Understand downstream requirements
Apply CI/CD best practices
Apply infrastructure-as-code
Participate in data governance
Manage access control
Document data platform
How You'll Work.
Team & Collaboration
Data consumers; Analytics Engineers
Process & Methodology
CI/CD, Infrastructure-as-code
Full Job Description
About the project: You will be embedded in the Data Platform team of a global mining organization, helping design and deliver a modern Azure-native data infrastructure. The team ingests data from dozens of operational sources — including REST and SOAP APIs, IoT sensors, ERP systems, and flat-file feeds — transforming it into curated, analytics-ready datasets that drive decisions across finance, operations, and supply chain. This is a hands-on engineering role. You will spend most of your time building and maintaining robust pipelines, optimizing data flows within Azure Synapse and Databricks, and ensuring the platform remains reliable, scalable, and secure. Key responsibilities: Gather and analyze business requirements to identify and prioritize integration opportunities. Design, build, and maintain scalable data pipelines using Azure Data Factory to orchestrate ingestion from diverse source systems. Develop and optimize data transformation logic and analytical workloads in Azure Synapse Analytics (dedicated and serverless SQL pools, Synapse Pipelines). Build and maintain Databricks notebooks and jobs (PySpark / Spark SQL) for large-scale data processing and feature engineering. Implement robust API extraction patterns — REST and SOAP — handling pagination, authentication (OAuth 2.0, API keys), rate limiting, and error recovery. Design and maintain the lakehouse architecture: raw, curated, and serving layers using Azure Data Lake Storage Gen2. Ensure data quality through validation frameworks, monitoring pipelines, alerting, and lineage documentation. Collaborate with Analytics Engineers and data consumers to understand downstream requirements and model data accordingly. Apply best practices for CI/CD, infrastructure-as-code (Azure DevOps, Terraform / Bicep), and environment management. Participate in data governance activities including metadata management, access control, and documentation. Requirements: 4+ years of experience in data engineering or a closely rela
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