Data Engineer

We are seeking a highly motivated and skilled Data Engineerto help us build and maintain efficient data architectures,pipelines, and reporting solutions. The ideal candidate willhave a strong foundation in database management, ETLprocesses, and BI tools like Power BI and Tableau. You willwork closely with both technical and business stakeholdersto ensure our data is accessible, clean, and ready foranalysis.

Responsibilities:

• Design & Build Data Pipelines: Design and implementscalable and reliable ETL (Extract, Transform, Load)processes to gather data from multiple sources andintegrate them into centralized data warehouses or lakes.
• Database Management: Manage relational and non-relationaldatabases, ensuring data integrity, security, andaccessibility. Optimize SQL queries for performance andefficient data retrieval.
• Business Intelligence & Reporting: Develop and maintaininteractive dashboards and reports using Power BI andTableau.
• Data Transformation & Modeling: Cleanse, transform, andstructure raw data into formats suitable for analysis.Develop efficient data models that enhance the performanceof BI tools.
• Monitor & Optimize Data Pipelines: Continuously monitorthe performance and reliability of data pipelines,troubleshoot issues, and implement improvements for betterscalability.
• Collaborate with Teams: Work closely with data scientists,analysts, and business teams to understand reporting needsand provide insights into business performance.
• Ensure data-driven decisions are based on accurate andwell-structured data.
• Ensure the dashboards are intuitive, user-friendly, anddeliver actionable insights to business stakeholders.
• Data Governance: Adhere to best practices for datagovernance, ensuring compliance with security protocolsand data privacy standards.

Requirements:

• Power BI & Tableau: Hands-on experience buildingdashboards and reports using Power BI and Tableau.
• Proficiency in creating advanced visualizations, reports,and KPIs.
• Database Expertise: Strong knowledge of SQL and experienceworking with relational databases (e.g., SQL Server,PostgreSQL) and NoSQL databases (e.g., MongoDB,Cassandra).
• ETL Tools & Data Integration: Familiarity with ETL tools(Azure Data Factory, Talend, Apache NiFi) for dataextraction, transformation, and loading.
• Experience building data pipelines from scratch.
• Data Warehousing Solutions: Knowledge of data warehousingconcepts and platforms (e.g., Snowflake, Amazon Redshift,Google BigQuery).
• Cloud Technologies: Experience with cloud platforms likeAWS, Azure, or Google Cloud for data storage, processing,and analysis.
• Programming Languages: Experience in Python or R for datawrangling, transformation, and analysis.
• Version Control: Experience with version control toolslike Git to manage and track changes in scripts and code.
• Strong problem-solving and analytical skills, withattention to detail.
• Excellent communication skills, both written and verbal.