Sr. Data and Analytics Engineer

Key Responsibilities: 

• Design, develop, and optimize data pipelines and ETL processes for efficient data ingestion, transformation, and integration from multiple sources. 

• Manage and maintain data warehouses and data lakes, ensuring accuracy, availability, and security. 

• Work closely with business stakeholders, data analysts, and data scientists to translate business needs into technical solutions. 

• Implement data quality frameworks, monitoring systems, and performance tuning. 

• Contribute to data modeling, architecture, and governance best practices. 

• Support the development of dashboards, reports, and analytical models to provide actionable insights. 

• Mentor junior engineers and foster a culture of collaboration and technical excellence within the data team. 

 Skills & Qualifications: 

• Strong experience in SQL, Python. Familiarity with data warehousing technologies (e.g., Snowflake, Redshift, BigQuery) and ETL tools (e.g., Apache Airflow, Talend, Fivetran). 

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

• Knowledge of cloud-based platforms (AWS, Google Cloud, Azure) and associated data services. 

• Experience with Hadoop, Spark, Kafka, or other big data technologies is a plus. 

• Strong understanding of relational databases, data modeling concepts, and designing data architectures. 

• Ability to analyze complex data sets and identify trends, correlations, and insights. 

• Excellent verbal and written communication skills, with the ability to explain complex data concepts to non-technical stakeholders. 

Experience: 

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’s preferred). 

• 4+ years of experience in data engineering or a related field, preferably in analytics or business intelligence. 

• Strong experience working with large datasets and complex data pipelines. 

• Previous experience in a similar industry or field is a plus. 

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