SENIOR DATA ENGINEER - SQL

A successful Business Data Analyst/consultant will have a strong analytical mindset, excellent communication skills, and the ability to work collaboratively with cross-functional teams to drive business results. Additionally, a Business Data Consultant/ Analyst should have expertise in data analysis tools and techniques, such as SQL, Excel, and statistical software, and have a deep understanding of data management and quality control processes.

Data Management and Strategies:

• Data Consulting: Provide consultative guidance for data management, governance, reporting/analytics within the company as well as for clients
• Data Collection: Gather data from various sources, including databases, spreadsheets, and other systems, and ensure data accuracy and completeness
• Data Analysis: Conduct data analysis using statistical and data visualization techniques to identify trends, patterns, and insights that can inform business decisions
• Data Interpretation: Translate complex data sets into understandable insights and actionable recommendations for business stakeholders
• Report Creation: Create reports and dashboards that summarize key insights and metrics for stakeholders across the organization
• Data Maintenance: Maintain and update databases and other data sources to ensure accuracy and completeness over time
• Data Quality Control: Ensure data quality by developing and implementing quality control procedures, including data validation, cleaning, and normalization
• Frameworks and Methodologies: Create Data Landscape frameworks, operating models and information process flows
• Collaboration: Work closely with cross-functional teams, including marketing, product, and finance, to provide data-driven insights and support decision-making
• Industry Knowledge: Stay up to date with industry trends and best practices related to data analysis and business intelligence

Technology Acumen :

• Technology Orientation: Exposure: know how to cloud Data tools and technologies and architecture patterns
• Technology Orientation: Exposure to at least one Cloud environment like Azure/AWS/GCP
• Technology Orientation: Exposure at least one of the data management platforms (Data Lakehouse/ Data lake / Data warehousing/Data Fabric)
• Technology Exposure: Hands on exposure to SQL/Python/Scala/python or at least any one of the programming languages
• Program Management: Good expertise/exposure in Data or Enterprise Transformation programs and project management

Soft skills :

• Communication: Communicate findings and insights clearly and effectively to both technical and non-technical stakeholders
• Communication: Excellent presentation and writing skills
• Cross-sell and deliver on data projects for key clients, growing revenue and producing case studies to promote the data science service
• Continuous Improvement: Continuously evaluate and improve data analysis processes and methodologies to optimize insights and outcomes.
• Continuous Improvement: Train and mentor team members in data input, use, meaning, and analysis
• Continuous Improvement: Research and make recommendations for training, equipment, and technology to improve data use