Data & Analytics Lead

at; Österreich; Vor Ort; EUR 80 000 - 100 000; Vollzeit

Zusammenfassung

A leading mining firm in Austria is seeking a Data & Analytics Lead to own their data platform and drive analytics across the organization. The role requires deep knowledge of Azure Data Platform and Power BI, coupled with strong leadership skills for managing outsourced teams. The ideal candidate will have 8+ years of experience in data engineering, with a proven track record of delivering impactful data solutions.

Aufgaben

• Build and maintain data pipelines using Azure Data Factory.
• Develop dashboards and reports in Power BI.
• Write efficient SQL and Python code for transformations.
• Deliver rapid prototypes and MVPs.
• Lead and manage the outsourced data engineering team.
• Establish data governance and quality processes.
• Work with stakeholders to identify and prioritize use cases.

Kenntnisse

Azure Data Platform

Data warehousing

Power BI

SQL

Python

Data governance

Stakeholder engagement

Analytical skills

Ausbildung

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering

Tools

Azure Data Factory

Databricks

SAP

Jobbeschreibung

Stanmore is a progressive leader in the coal mining industry, dedicated to technological innovation, sustainability, and operational excellence. As part of our digital transformation journey, we are seeking a dynamic, hands-on Data & Analytics Lead to take full ownership of our data platform, analytics, and reporting landscape.

This is a unique opportunity to combine technical expertise (building pipelines, models, and dashboards) with leadership of outsourced teams and close collaboration with the business and driving real impact from data across the organisation.

Overview

As Data & Analytics Lead, reporting to our Enterprise Systems Manager, you will own the data platform, analytics, and reporting landscape and drive value from data across the organization.

Responsibilities

• Build and maintain data pipelines using Azure Data Factory, Synapse, Data Lake, and Fabric.
• Develop dashboards and reports in Power BI – from raw data modelling to business-ready insights.
• Write efficient SQL and Python code for transformations, analysis, and automation.
• Deliver rapid prototypes and MVPs that show early value, with a pathway to scale.
• Apply data science techniques pragmatically (e.g., anomaly detection, predictive modelling) where they add business value.

Leadership

• Operational ownership of the data environment, ensuring stability, performance, and security.
• Own the data platform backlog and ensure priorities are delivered on time.
• Lead and manage the outsourced data engineering/vendor team, providing direction, setting standards, and reviewing outputs.
• Establish and enforce data governance, quality, and lineage processes.
• Act as the subject-matter lead for data architecture, warehousing, and integrations across SaaS and on-premise systems (e.g. Minestar, SAP, ServiceNow, and other enterprise platforms).
• Ensure alignment of data initiatives with enterprise architecture and data governance standards.

Business Engagement

• Work with stakeholders to identify, frame, and prioritise use cases aligned to business goals.
• Translate technical outputs into clear business outcomes (ROI, cost reduction, operational efficiency).
• Build credibility with senior leaders by communicating insights and progress effectively.

To be a success it is expected you will have

• Strong technical background in the Azure Data Platform (ADF, Synapse, Data Lake, Fabric, Databricks desirable).
• Very strong data warehouse experience (cloud & on-premise).
• Proficient in Power BI, capable of independently delivering comprehensive reporting solutions.
• Efficient in data modelling, data analysis and data profiling.
• Advanced SQL and Python.
• Strong track record in data platform leadership, owning a backlog, prioritising, and delivering through a combination of hands-on work and vendor management.
• Proven track record of leading outsourced/offshore teams or small internal teams.
• Demonstrated ability to deliver tangible outputs quickly, not just long-term projects.
• Hands-on: doesn’t just delegate, can deliver independently when needed.
• Ability to bridge strategy and execution: translating business needs into technical delivery without losing focus on outcomes.
• Proven experience with data governance, metadata management, and lifecycle processes.
• Excellent stakeholder engagement – able to work with both technical teams and business leaders.

Experience

• 8+ years of experience in data engineering, architecture, or a similar role, preferably in the mining or heavy industry sector.
• Proven track record of deploying data solutions in large-scale industrial settings.
• Exposure to AI/ML tools and applied analytics use cases.
• Knowledge of SAP data structures and reporting.

Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication skills with the ability to convey technical concepts to non-technical audiences.
• Leadership and collaboration skills to manage multi-disciplinary teams.

Education

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.