​​Software Engineer​

vor 3 Wochen

Geneva, Schweiz Microsoft Vollzeit

Overview

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world. Microsoft’s Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. The products our portfolio include Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. ​​Within Azure Data, the data integration team builds data gravity on the Microsoft Cloud. Massive volumes of data are generated – not just from transactional systems of record, but also from the world around us. Our data integration products – Azure Data Factory and Power Query make it easy for customers to bring in, clean, shape, and join data, to extract intelligence.​ ​​We’re the team that developed the Mashup Engine (M), Power Query, M Connectors and the Data Gateway. We already ship monthly to millions of users across Excel, Power BI, Microsoft Fabric, Flow, and PowerApps; but in many ways we’re just getting started. We’re building new services, experiences, and engine capabilities that will broaden the reach of our technologies to several new areas – automated dataflows, data “intelligence”, and large-scale data analytics. We plan to use example-based interaction and innovative visualization to make data access and transformation even more intuitive for non-technical users. If the “democratization of data” sounds like a compelling mission, this is the team for you.  We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our customers are better served.

Qualifications

Required/Minimum Qualifications

· Bachelor's Degree in Computer Science, or related field or equivalent experience.

Additional or Preferred Qualifications

· Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) experience in business analytics, data science, data modeling or data engineering work

o OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field o OR equivalent experience.

#azdat

#azuredata

​​#powerquery #microsoftfabric​

Responsibilities

Data Requirements and Modeling

· Learns to collaborate with appropriate stakeholders and interprets data requirements. Assists senior leaders with the assessment of project costs, access, usage, use cases, and availability for business or customer scenarios related to a product feature. Learns about the feasibility of data needs and supports team members by finding alternative options if requirements cannot be met. Utilizes relevant data metrics or measures to assess data across varied service lines.

· Supports the appropriate data model for the project and reviews design specification documents to model the flow and storage of data with guidance from senior colleagues. Works closely with team members to identify basic improvements to design specifications, data models, or data schemas, leveraging feedback from the Program Manager, so that data is easy to connect, ingest, has a clear lineage, and is responsive to work with. Demonstrates knowledge of analytical requirements and compute/storage consumption for data and documents the cadence of data extraction, transformation, and loading into simple, data products or datasets in cloud and local environments. Demonstrates awareness of costs associated with data that are used to assess the total cost of ownership (TOC).

Data Management and Transformation

· With detailed instructions, implements basic code to extract raw data from identified upstream sources using common query languages, according to clearly written documentation. Participates in code reviews and consults with other team members to better understand and apply advanced concepts. Uses knowledge of the data use cases to contribute to basic orchestration techniques that automate

data extraction logic, under the direction of others. Uses simple data protocols to validate the quality and reliability of extracted data at the time of acquisition and at the output of data, consistent with the Service Level Agreement. Records, tracks, and maintains data source control and versioning, requesting feedback from other team members as needed. Applies knowledge of data to validate that the correct data is ingested and that the data is applied accurately within the area of work.

· Applies basic modification techniques and operations (e.g., inserting, aggregating, joining) to transform raw data into a form that is compatible with downstream data sources, databases, and formats, following detailed instructions. Assists with efforts to use software, query languages, and computing tools to transform raw data, as requested. Uses protocols to assess data quality and completeness using queries and basic statistical techniques. Works with others to merge data into distributed systems, products, or tools for further processing.

· Contributes to the development and use of data tools that are used to transform, manage, and access data, with guidance from others. Contributes to and validates code to test storage and availability of data platforms and assists others with the implementation of sustainable design patterns to make data platforms more usable and robust to failure and change. Performs supervised work to analyze relevant data sources that allow others to develop insights into data architecture designs or solution fixes.

Engineering Fundamentals

· Contributes to performance monitoring protocols across a data pipeline. Supports existing visualizations and smart aggregations to monitor data quality and pipeline health to ensure pipeline performance. Follows troubleshooting guides (TSGs) and operating procedures for reviewing, addressing, and/or fixing basic problems/anomalies flagged by automated testing. Contributes to the support and monitoring of platforms.

· Assists with root cause analysis in response to detected problems/anomalies to identify the reason for alerts and assist others to implement basic solutions that minimize points of failure. Helps others implement and test improvements across a product feature to retain data quality and optimal performance (e.g., latency, cost) throughout the data lifecycle. Performs supervised work to draft documentation of the problem and solution through postmortem reports and shares insights with the immediate team. Begins to learn about pipelines, data products, and service level agreements (SLAs) across assigned workstreams.

Compliance

· Follows data modeling and data handling procedures to maintain compliance with applicable laws and policies across assigned workstreams. Learns about processes used to tag data based on categorization. Demonstrates knowledge of data types, classifications, and lineage to ensure traceability. Learns about permissions and approvals for data access within a data pipeline(s). Contributes to the relevant data glossary to document the origin, usage, and format of data for each program.

Other · Embody our culture and values

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect

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