Data Engineer

✔️ Expertise in designing, building, and maintaining scalable data pipelines and architectures for efficient data ingestion, processing, and storage.
✔️ Strong experience with ETL/ELT processes using tools like Apache Airflow, Talend, Informatica, or custom Python/Scala solutions.
✔️ Proficiency in working with large datasets across structured, semi-structured, and unstructured formats, optimizing for performance and reliability.
✔️ Deep knowledge of SQL and database systems such as PostgreSQL, MySQL, Snowflake, Redshift, BigQuery, and NoSQL databases like MongoDB and Cassandra.
✔️ Ability to work with big data technologies such as Hadoop, Spark, Kafka, and distributed data processing frameworks.
✔️ Experience in developing and maintaining cloud-based data solutions on platforms like AWS (Glue, Redshift, S3), Azure (Data Lake, Synapse), or GCP (BigQuery, Dataflow).
✔️ Strong understanding of data modeling, data warehousing concepts, star/snowflake schema design, and OLAP/OLTP systems.
✔️ Ability to build and maintain APIs for data access, real-time data integration, and automation processes.
✔️ Expertise in ensuring data quality, data governance, and implementing best practices for data security, lineage, and compliance (GDPR, HIPAA).
✔️ Ability to troubleshoot, debug, and optimize complex data pipelines and queries to improve performance and reduce costs.
✔️ Experience in working with data orchestration, workflow scheduling, and real-time data streaming platforms.
✔️ Proficiency in programming languages like Python, Java, or Scala for data engineering tasks and automation.
✔️ Strong collaboration skills to work closely with data scientists, analysts, and business stakeholders to deliver robust data solutions.
✔️ Ability to support internal teams with best practices in data engineering, data platform management, and analytics integration.
✔️ Languages: English proficiency (additional language skills are a plus).