Data Analyst

We are seeking a detail-oriented and analytical Data Analyst to support data-driven decision-making across multiple departments.

This role involves working with large datasets, developing SQL queries, performing ETL processes, and creating actionable insights through data visualization and statistical analysis.

The ideal candidate will have a strong background in data analytics, problem-solving, and stakeholder collaboration.

Key Responsibilities

Develop and analyze SQL queries to reflect business rules and data requirements.

Extract, transform, and load (ETL) data from various sources, ensuring data accuracy and integrity.

Perform data cleansing, validation, and preprocessing to prepare structured and unstructured data for analysis.

Develop and execute queries, scripts, and data manipulations using SQL, Python, or other relevant tools.

Identify trends, patterns, and correlations within large datasets to support strategic decision-making.

Create data visualizations, dashboards, and reports using tools like Tableau, Power BI, or Looker.

Collaborate with clients and cross-functional teams to understand data requirements and provide actionable insights.

Work closely with Data Scientists and Engineers to support predictive modeling, machine learning, and statistical analysis.

Monitor and improve data quality, proactively identifying anomalies and discrepancies.

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

Identify and implement process improvements to enhance data workflows and analysis efficiency.

Required Qualifications

3+ years of experience with data analysis tools such as Excel, SQL, R, Python.

3+ years of experience supporting Software Engineering, Data Engineering, or Data Analytics projects.

2+ years of experience leading a team supporting data-related projects.

Travel : Ability to travel at least 25% as needed.

Preferred Qualifications

Proficiency in data visualization tools such as Tableau, Power BI, or Looker.

Experience with cloud data platforms like AWS Redshift, Google BigQuery, or Azure Synapse.

Strong understanding of ETL processes and data pipeline development.

Knowledge of machine learning techniques and predictive analytics.

Experience in industries such as financial services, healthcare, or manufacturing is a plus.

Understanding of data governance and data privacy regulations.

Ability to query and manipulate databases and data warehouses efficiently.

Excellent communication and problem-solving skills, with the ability to translate data insights for non-technical stakeholders.

Detail-oriented mindset, ensuring accuracy and reliability of analytical outputs.

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