Talent Pool: Lead/Senior Data Engineer

Responsibilities

• Data organization and analysis: handling structured, semi-structured, unstructured, and image-based data.
• Building data systems and pipelines
• Preparing data for prescriptive and predictive modeling
• Designing end-to-end pipelines within a hybrid big data architecture, using Cloud Native AWS, Python, SQL, etc.
• Leveraging AWS Cloud services for building data pipelines and ensuring effective monitoring
• Collaborating with data scientists and architects across various projects

Requirements

• 7+ years of Data Engineering experience utilizing designated technologies and tools.
• Profound knowledge and hands-on experience with Python (Pandas, boto3), SQL, Spark, Databricks, DWH
• Proficient use of orchestrators such as Airflow
• Expertise with AWS services essential for Data Engineering: AWS Glue, AWS Lambda, S3, RDS, Redshift, Athena, SQS, SNS, etc.
• Ability to write robust code with Python.
• Deep understanding of pub-sub architecture
• Strong upper-intermediate or higher (B2+) proficiency in English
• Solid analytical and problem-solving skills

Nice to have

• Experience with AWS Dynamo DB, Aurora (including serverless nuances), Elasticache, Kinesis services, Neptune
• Familiarity with AWS Networking
• Familiarity with Azure 
• Experience with Snowflake

We offer

• Competitive compensation
• Remote or office work
• Flexible working hours
• Healthcare benefits: medical insurance and paid sick leave
• Continuous education, mentoring, and professional development programs
• A team with an excellent tech expertise
• Certifications paid by the company