Data Observability Consultant- Freelancer

About our Team  

The Data Technology Consulting Practice is responsible for building modern and innovative technology services which enable our customers to successfully deliver value from data. Currently, the Practice focuses on four data technology domains:  

• Data strategy: How to deliver a structured approach to design and execute data and analytics programs which are linked to an organization’s business strategy ?  

• Data management: How to govern and manage data more efficiently, enabling organizations to achieve better business outcomes ? How to optimize existing data platform architectures and technology designs to improve technical and cost performance? 

• Data consumption: How to enable visual data communication in organizations and realize value from data through actionable insights which deliver value  ? 

Who we are looking for  

We are looking for a data observability consultant who will help mature data quality and observability offerings and lead data observability initiatives for customers.  The position will report to the head of Data consulting practice. This is a high visibility role with plenty of opportunities to enhance your skillset and build your career working for Fortune Global 500 companies.  

Responsibilities  

• Data Observability Management: Define end-to-end data quality and observability solution including data quality operating model and framework using relevant Data Observability tools such as, but not limited to, Acceldata, Anomalo, BigEye, Soda, Monte Carlo etc.   

• Data Observability: Lead development and deployment of off-the-shelf or be-spoke solutions that monitor data pipelines and databases with help of automated checks and alerts. 

• Data Quality Improvement: Develop and implement reactive, predictive, and preventive strategies to improve the quality of data in the data analytics products and platforms using various methods including data cleansing, data enrichment, data validation, data observability and AI/ML. 

• Collaboration: Collaborate with data engineers, data scientists, and other stakeholders to ensure data quality across all stages of the data lifecycle. 

• Innovation in Data Quality & Observability: Stay abreast of industry trends and emerging technologies. Propose innovative solutions to enhance data observability processes. Experiment with novel approaches and tools to optimize data quality outcomes. 

• Liaise with information security teams, and business data stewards, to define priorities and roadmaps for managing and mitigating risks related to data security and data privacy. 

• Drive upskilling and adoption initiatives on data observability within customer organizations. 

• Contribute to balanced score cards as well as data collection and reporting process for data governance councils for monitoring progress and tracking bottlenecks. 

• Identify and define opportunities for automating data quality related processes. 

• Collaborate with other Data Management consultants at Lingaro to identify and create repeatable methodologies and templates for effectively delivering data management and governance services.  

• Collaborate with colleagues in different timezones to build integrated offerings for customers. 

• Collaborate with Lingaro’s technology and delivery teams for implementation of data management and governance solutions. 

 Required Skills, Knowledge and Experience  

• Bachelor’s degree in any quantitative discipline.  

• 7 to 10 years of experience in implementing off-the-shelf or be-spoke data observability solutions.   

• Proven experience with data observability tools such as Acceldata, BigEye, Soda, Monte Carlo, Anomalo etc. Or experience implementing bespoke observability solutions using Grafana, Prometheus or cloud native services. 

• Proven experience as a Data Quality Consultant, Data Quality Engineer or similar role. 

• Proficiency in SQL and other programming languages such as Python or R. 

• Ability to clearly articulate, influence, and thought partner with senior business leaders. 

• Understanding of modern technology trends and data stacks in data management and governance.  

• Experience in running customer workshops and other collaboration sessions to discover customer priorities, understand current state, and determine maturity/readiness to execute on enterprise Data Management & Governance vision. 

• Familiarity with Azure, or GCP and associated DQ capabilities. Understanding of cloud-based data storage and data pipeline architecture. 

Good to Have Skills: 

• Project Management: Experience in working closely with clients to understand their data quality needs and execute projects to meet these needs. This includes defining project scope, developing project plans, and ensuring projects are delivered on time and within budget. 

• Data Visualization Tools: Familiarity with data visualization tools like Tableau, PowerBI, etc., to represent data quality metrics and insights. 

Nice to Have Skills: 

• Experience with data quality tools such as Informatica, Talend, Collibra, Precisely, Ataccama, FirstEigen, Validio, Great Expectations etc. 

• Machine Learning: Basic understanding of machine learning algorithms can help in building predictive models for data quality. 

• Certifications: Certifications in Azure, GCP, or AWS can be a plus. 

• Experience in Master data management projects. 

• Understanding of frameworks such as DAMA, DCAM, and any relevant certifications.