About the Job:
The company is seeking a highly skilled and qualified Senior Data Engineer to assess, analyze, and work with complex data concepts and new data sources to provide business insights. You will play a critical role in the implementation and integration of these data sources into the company platform.
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Key Responsibilities:
- Solve challenging problems using Python coding skills.
- Design, build, and launch new data extraction, transformation, and loading (ETL) processes in production.
- Engage in web crawling, data cleaning, data annotation, data ingestion, and data processing.
- Read and collate complex data sets.
- Create and maintain data pipelines.
- Focus on continuous process improvement to drive efficiency and productivity within the team.
- Utilize Python, SQL, Elasticsearch, and Shell to build optimal infrastructure for data extraction, transformation, and loading.
- Build analytical tools that utilize the data pipeline to provide insights into key business performance metrics.
- Support the broader business with their data needs on an ad hoc basis.
- Ensure compliance with QHSE (Quality Health Safety and Environment), Business Continuity, Information Security, Privacy, Risk, Compliance Management, and Governance of Organizations policies and procedures.
Qualifications:
- Bachelor's degree in Computer Engineering, Computer Science, or Electrical Engineering and Computer Sciences.
- 6+ years of programming experience, with solid coding skills in Python, Shell, and Java.
- Strong corporate capacity and communication skills.
- Experience with web crawling and data cleaning.
- Proficient in solution architecture, data ingestion, query optimization, ETL/ELT processes, AWS (EC2, S3, SQS, Lambda), Elasticsearch, Redshift, and CI/CD frameworks.
- Working knowledge of data platform concepts including data lakes and data warehouses, and real-time processing architecture.
- Proficient in PostgreSQL and programming (preferably in Java and Python), with a solid understanding of structured and unstructured data, SQL, and NoSQL databases.
- Knowledge of best practices in optimizing columnar and distributed data processing systems.
- Experience in designing and implementing dimensional modeling.
- Familiarity with machine learning and data mining techniques in areas such as statistical modeling, text mining, and information retrieval.
Language Requirements:
- Proficiency in English is required; additional languages may be beneficial.
