Senior Data & 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.

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.

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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