MSP Data & Automation Solutions Engineer at MSPbots

, , Namibia -

Full Time

Start Date

Immediate

Expiry Date

31 Mar, 26

Salary

0.0

Posted On

31 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Integration, API, Automation, SQL, Data Visualization, RPA, Power BI, Tableau, Python, PowerShell, Communication, Data Governance, Business Analysis, Technical Solutions, Real-Time Data, Data Accuracy

Industry

IT Services and IT Consulting

Description

Overview This role is crucial within the company's technical service system, responsible for streamlining the data flow within the core ecosystem of MSPs (Managed Service Providers). You will leverage APIs and automation tools from both a business and technical perspective to transform fragmented data scattered across PSA, RMM, and document systems into real-time, accurate decision-making data. You will not only be a data "extractor" but also a "translator" of customer business needs and a "builder" of process automation. Core Responsibilities: 1. Heterogeneous System Data Integration and Vendor Collaboration In-depth Data Extraction: Based on an understanding of the data structures of mainstream MSP tools (such as ConnectWise, Autotask, NinjaOne, ITGlue, etc.), design and execute efficient data scraping solutions. External Technical Liaison: Act as the technical contact for third-party software vendors, independently resolving issues such as API authorization, restricted interface calls, or data synchronization anomalies without directly accessing the backend to modify configurations. Interface Stability Monitoring: Establish a monitoring mechanism to ensure the stability of the data scraping process and adjust scraping strategies promptly based on updates to third-party systems. 2. High-Quality Real-Time Data Governance Real-Time Assurance: Utilize technologies such as Webhooks and streaming processing to minimize latency from data generation to display, meeting stringent customer requirements for "real-time monitoring." Data Accuracy Calibration: Establish rigorous data verification logic to ensure 100% consistency between report data and original system data, maintaining data integrity. 3. Customer Needs Analysis and Solution Consulting Business Needs Analysis: Directly engage with clients, guiding and uncovering their true needs in areas such as operational monitoring, SLA analysis, and resource billing. Technical Solution Transformation: Translate clients' business language into technical feasibility reports, indicator definition documents, and RPA process logic diagrams. 4. Data Visualization and RPA Development BI Report Delivery: Utilize tools such as Power BI and Tableau to build interactive, real-time visual dashboards for clients. Automated Process Implementation: Design and develop RPA (Robotic Process Automation) solutions for clients' repetitive, cross-system operation scenarios, significantly improving client operational efficiency. Job Requirements: 1. Industry Experience and Background Familiar with the business logic of the MSP industry (e.g., work order flow, asset management, remote monitoring, monthly settlement, etc.). At least 2 years of experience in data development, system integration, or technical services. 2. Technical Skills API Expert: Proficient in RESTful API calls, able to handle JSON/XML data skillfully, and familiar with authentication protocols such as OAuth2. SQL & Modeling: Proficient in SQL writing and capable of cross-system data modeling. BI/RPA Tools: Proficient in at least one mainstream BI tool (such as Power BI) and one automation tool (such as Power Automate, Make, UI Path, etc.). Scripting Skills: Basic Python or PowerShell skills; able to write simple data cleaning or auxiliary scripts. 3. Core Soft Skills Effective Communicator: Able to communicate smoothly with technical support from overseas software vendors and explain technical solutions to clients in a clear and understandable way. Logical Rigor: Extremely sensitive to data logic, able to identify and resolve subtle deviations in complex data chains. Job Evaluation Criteria (KPI Example) Data Accuracy: The degree of consistency between report data and source system data. Real-time Metrics: The average time from triggering core business data to data entry/display. Customer Satisfaction: Whether the delivered reports and automated processes accurately address customer pain points.

Responsibilities

The role involves integrating heterogeneous system data and collaborating with vendors to ensure data flow stability. Additionally, it includes analyzing customer needs and delivering automated solutions for operational efficiency.