Data Engineer

• Experience: 6 to 10 years of professional experience in data engineering, backend software engineering, or a closely related field.
• Programming Mastery: Strong proficiency in at least one primary data programming language, preferably Python, Scala, or Java.
• Advanced SQL: Deep expertise in writing complex, highly optimized SQL queries and understanding relational database engines.
• Data Modeling: Solid understanding of data warehousing concepts, dimensional modeling, and database design principles.
• ETL/ELT Fundamentals: Proven experience building batch processing pipelines and integrating data from disparate sources.
• Version Control and Best Practices: Experience with Git, code reviews, writing unit tests, and CI/CD principles.

Preferred / Specialist Skills (Optional):

• We do not expect you to know everything. Experience with at least one tool from the categories below is highly preferred:
• Enterprise ETL and Data Integration: Hands-on experience with enterprise-grade integration tools like Informatica, Talend, Pentaho, OR IBM DataStage.
• Cloud Platforms: Experience with AWS (e. g., S3 RDS), GCP (e. g., Cloud Storage), OR Azure.
• Cloud Data Warehouses: Familiarity with Snowflake, Google BigQuery, OR Amazon Redshift.
• Distributed Processing: Hands-on experience with Apache Spark, Databricks, OR Hadoop/Hive.
• Pipeline Orchestration: Knowledge of scheduling and dependency management using Apache Airflow, Dagster, OR Prefect.
• Streaming / Real-Time Data: Experience with message brokers and streaming tools like Apache Kafka, AWS Kinesis, OR GCP Pub/Sub.
• Infrastructure as Code (IaC): Familiarity with deploying infrastructure using Terraform OR AWS CloudFormation.