Senior Data Analyst

Job Description

The ideal candidate should possess strong data manipulation skills, a keen eye for detail, and the ability to work with diverse datasets. This role plays a crucial part in ensuring the quality and integrity of our data, enabling informed decision-making across the organization.

• Data Acquisition: Retrieve and collect raw data from various sources, including databases, APIs, and external datasets. Assess data quality and completeness during the acquisition phase.
• Data Cleaning: Cleanse and preprocess data to identify and rectify errors, inconsistencies, and missing information. Standardize and validate data to ensure accuracy and conformity to defined data standards.
• Data Transformation: Perform data transformations to convert raw data into usable formats, utilizing tools such as SQL, Python, or other data wrangling tools. Implement data enrichment and normalization processes.
• Data Integration:Integrate disparate datasets to create a unified and comprehensive view of the data. Merge, join, and concatenate datasets as needed to meet business requirements.
• Quality Assurance: Conduct thorough quality checks on processed data to ensure adherence to data quality standards. Collaborate with data engineers and analysts to validate and verify the accuracy of data transformations.
• Documentation: Maintain detailed documentation of data wrangling processes, including data sources, cleaning methodologies, and transformation logic. Communicate and document any anomalies or challenges encountered during the data wrangling process.
• Collaboration: Work closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver solutions. Collaborate with IT teams to optimize data extraction, transformation, and loading (ETL) processes.

• Experience working with big data technologies (e.g., Hadoop, Spark).
• Knowledge of machine learning concepts and techniques.
• Previous experience in industries with complex and varied datasets.
• Critical thinking and analytical skills.
• Ability to manage multiple priorities and meet deadlines in a fast-paced environment.
• Aptitude for learning technology (proprietary tools)
• Strong written and verbal English language communication skills.
• A process-improvement and knowledge sharing mindset.
• Execute effectively in cross-cultural business settings.
• Experience working with an outsourcing work stream or in shared service environment required.
• Strong proficiency with MS Office suite, Power BI or Tableau Data Analytics tool

• 3 -5 years of relevant experience.
• Bachelors degree in Computer Science, Statistics, Information Technology, or a related field.
• Proficiency in using data wrangling tools such as SQL, Python, R, Alteryx or specialized data preparation platforms.