As a Data Engineer, you will play a key role in designing, developing, and optimizing data pipelines and storage solutions in a complex, enterprise-scale data warehouse environment. You will contribute to full life-cycle software development projects, leveraging modern technologies and best practices to deliver high-quality, actionable data solutions.

Key Responsibilities:

- Participate in the full software development lifecycle for enterprise data projects, from requirements gathering to deployment and support.

- Design, develop, and maintain robust ETL processes and data pipelines using Snowflake, Hadoop, Databricks, and other modern data platforms.

- Work with a variety of databases: SQL (MySQL, Postgres SQL, Vertica), NoSQL (MongoDB, Cassandra, Azure Cosmos DB), and distributed/big data solutions (Apache Spark, Cloudera).

- Write advanced SQL queries and perform complex data analysis for business insights and operational reporting.

- Develop scripts in Python and shell for data manipulation, automation, and orchestration.

- Perform data modelling, analysis, and preparation to support business intelligence and analytics solutions.

- Maintain and optimize Unix/Linux file systems and shell scripts.

- Collaborate with cross-functional teams to translate business requirements into scalable data solutions.

- Present analytical results and recommendations to technical and non-technical stakeholders, supporting data-driven decision making.

- Troubleshoot, diagnose, and resolve complex technical issues across the data stack.

- Stay current with industry trends, tools, and best practices to continuously improve data engineering processes.

Required Skills and Qualifications:

- Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent experience).

- Demonstrated full life-cycle experience in enterprise software/data engineering projects.

- Hands-on experience with Snowflake and Hadoop platforms.

- Proficient in SQL, Postgres SQL, Vertica, and data analysis techniques.

- Experience with at least one SQL database (MySQL, Postgres SQL) and one NoSQL database (MongoDB, Cassandra, Azure Cosmos DB).

- Experience with distributed/big data platforms such as Apache Spark, Cloudera, Vertica, Databricks, or Snowflake.

- Extensive experience in ETL, shell or Python scripting, data modelling, analysis, and data preparation.

- Proficient in Unix/Linux systems, file systems, and shell scripting.

- Strong problem-solving and analytical skills.

- Ability to work independently and collaboratively as part of a team; proactive in driving business decisions and taking ownership of deliverables.

- Excellent communication skills with experience in presentation design, development, and delivery to communicate technical insights and recommendations effectively.

Preferred/Desirable Skills:

- Industry certifications in Snowflake, Databricks, or Azure Hyperscale are a strong plus.

- Experience with cloud platforms such as AWS, Azure, or Snowflake.

- Familiarity with BI reporting tools like Power BI or Tableau.

- Proficient in using Git for branching, merging, rebasing, and resolving conflicts in both individual and team-based projects.

- Familiar with GitHub Copilot to accelerate code writing, refactoring, and documentation tasks.

- Knowledge of industry best practices and emerging technologies in data engineering and analytics.