Senior Data Consultant

Role Overview:

We are looking for a Senior Data Consultant to work with business and technical stakeholders to solve complex data, analytics, and reporting challenges.

The role involves understanding business requirements, translating them into data-driven solutions, performing advanced analysis, and supporting the design and implementation of scalable data solutions.

Key Responsibilities:

- Work closely with clients and business stakeholders to understand data, reporting, and analytics requirements.

- Translate business problems into structured data and analytical solutions.

- Analyze large and complex datasets to identify trends, patterns, anomalies, and actionable insights.

- Develop complex SQL queries for data extraction, transformation, validation, and analysis.

- Support the design of data models, data structures, and analytical frameworks based on business requirements.

- Work with data engineering teams to define data requirements and ensure availability and quality of required datasets.

- Develop and maintain dashboards, reports, and analytical solutions using relevant BI and visualization tools.

- Perform data profiling, cleansing, reconciliation, and validation to ensure data accuracy and consistency.

- Identify data quality issues and work with technical teams to investigate and resolve root causes.

- Support ETL/ELT processes and data integration initiatives across multiple data sources.

- Conduct exploratory and descriptive analysis to support business decision-making.

- Convert analytical findings into clear business recommendations and communicate them effectively to stakeholders.

- Participate in requirement gathering, solution design, documentation, testing, and implementation activities.

- Prepare functional and technical documentation, including business requirements, data definitions, process flows, and solution specifications.

- Support UAT and coordinate with business users to validate analytical and reporting solutions.

- Monitor deployed data solutions and support troubleshooting and issue resolution.

- Contribute to improving data processes, reporting frameworks, analytical methodologies, and overall data maturity.

- Stay updated with emerging data technologies, analytics practices, and industry trends.

Technical Skills:

- 3 - 5 years of experience in Data Consulting, Data Analytics, Business Intelligence, Data Engineering, or a related field.

- Strong proficiency in SQL, including complex joins, subqueries, CTEs, window functions, aggregations, and query optimization.

- Strong understanding of data analysis, data modelling, data warehousing, and data management concepts.

- Hands-on experience working with structured and large-scale datasets.

- Experience with BI and data visualization tools such as Power BI, Tableau, or Looker.

- Good understanding of ETL/ELT processes and data integration concepts.

- Experience with data quality, validation, reconciliation, and data profiling.

- Familiarity with cloud data platforms such as AWS, Azure, GCP, Snowflake, or Databricks is preferred.

- Understanding of relational databases and data warehouse architectures.

- Exposure to analytics, statistical analysis, or advanced data science concepts is an added advantage.

- Familiarity with Agile methodologies, Jira, Git, or similar collaboration and version-control tools is preferred.

Consulting & Business Skills:

- Strong ability to understand business requirements and convert them into practical data solutions.

- Excellent analytical and problem-solving skills.

- Strong client-facing and stakeholder management capabilities.

- Ability to communicate complex data concepts in a simple and business-friendly manner.

- Ability to prepare and present insights, recommendations, and solution approaches to senior stakeholders.

- Strong attention to detail with a focus on data accuracy and quality.

- Ability to manage multiple priorities and deliver projects within defined timelines.

- Comfortable working in cross-functional teams involving business, analytics, engineering, and technology stakeholders.

Education:

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, Information Technology, Business Analytics, or a related discipline