The Data Engineer will play a key role in building and maintaining a modern data infrastructure. They will design, develop, and optimize ELT/ETL pipelines and implement efficient data models to support analytics, reporting, and business decision-making. The role involves deep collaboration with cross-functional teams to deliver scalable and high-performing data solutions using tools such as Snowflake, ADF, dbt, and Python.

Responsibilities include:

• Design, build, and maintain scalable and robust data pipelines using ELT/ETL patterns to ingest, transform, and integrate data
• Architect and implement efficient data models using Star, Snowflake, and One Wide Table (OWD) design patterns
• Maintain and create documentation of data architecture, data pipelines, and processes to ensure transparency and reproducibility
• Integrate data from multiple sources including databases, APIs, and third-party platforms using tools like Azure Data Factory (ADF) and dbt
• Lead technical discussions, advocate for best practices, and ensure solid data foundations and high standards in data engineering workflows
• Optimize data systems for performance and cost efficiency using partitioning, clustering, caching, indexing, and fine-tuning techniques
• Perform QA audits, manage data loads, generate memo files, and handle ad hoc data requests to ensure data integrity and reliability
• Support analytics and reporting by developing reusable metrics, dashboards, and self-service tools in Power BI and/or Sisense
• Enhance SDLC by incorporating CI/CD pipelines, version control (e.g., Git), and continuous improvement practices into data engineering processes
• Collaborate with internal and external stakeholders to gather requirements and deliver comprehensive data solutions
  
  

Education:

• Bachelor’s Degree in Computer Science, Mathematics, Statistics, Finance, Information systems or equivalent related technical field experience
  
  

Experience:

• 5+ years of professional experience in data engineering, data analytics, or a similar technical role
• Strong SQL skills with advanced knowledge of Joins, Unions, CTEs, Aggregations, Lag/Lead, and optimization techniques
• Proficiency in Python for data manipulation, scripting, and automation
• Experience working with Snowflake, dbt, and Azure Data Factory (ADF)
• Demonstrated experience in data modeling, including dimensional and modern approaches (Star, Snowflake, OWD)
• Hands-on experience in building and maintaining data pipelines (ETL/ELT)
• Understanding of cost optimization, caching, partitioning, and indexing strategies for performance tuning
• Familiarity with BI tools such as Power BI, Sisense, Looker, Tableau, and Domo
• Experience with customer personalization solutions and handling large datasets
• Exposure to scripting languages like Python, Perl, or Shell
  
  

Tools & Skills:

• Deep understanding of complex SQL and Snowflake SQL syntax, including Time Travel, Streams, Cloning, and Role-Based Access
• Strong knowledge of Snowflake, Azure Data Factory, and dbt
• Experience with version control systems and CI/CD workflows
• Knowledge of DataBricks (ADB preferred) and ability to interpret existing solutions
• Familiarity with reporting tools, especially Power BI and/or Sisense
• Advanced proficiency in Python and Excel for data analysis and transformation
• Understanding of data warehousing, proactive data quality monitoring, and structured/unstructured data formats including JSON
  
  

Key Competencies:

• Proven problem-solving skills and high attention to detail
• Ability to partner with business stakeholders to define questions and build data sets to answer them
• Capable of navigating ambiguity and balancing multiple priorities in a fast-paced environment
• Excellent communication and presentation skills for technical and non-technical audiences
• Self-starter with a spirit of innovation and consistent delivery
• Demonstrated ability to work collaboratively in multi-disciplinary teams and produce results quickly
  
  

Assets:

• Experience in Telecom or banking industries, especially related to data collection or retention
• Hands-on experience with ADF data transformations for custom reporting models
• Experience in scripting and automation using Python, Perl, or Shell
• Familiarity with data transformations using tools like dbt
• Data analysis, report development, and business analysis
• Experience with tools like Looker, Excel, Power BI, Tableau, R, SAS
  
  

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