Collaborate with Data Science teams, constructing datamarts, and addressing ad-hoc requests

Craft and sustain data pipelines, ETL processes, and REST APIs to optimize data processing and delivery

Ensure the scalability, efficiency, and reliability of our data solutions

Provide on-call support for uninterrupted operation of data solutions

Team up with cross-functional groups to deliver top-notch data solutions aligned with project objectives and timelines

Continuously assess industry trends and implement cutting-edge data engineering strategies

Provide guidance and mentorship to junior team members, fostering a culture of growth and perpetual learning

Engage directly with clients to comprehend their requirements and provide tailored, efficient solutions

Work closely with stakeholders, showcasing exceptional communication and leadership skills

At least 3 years of hands-on experience in Data Software Engineering, specializing in large-scale data projects and intricate data infrastructures

Proven track record in constructing and maintaining data pipelines, ETL processes, and REST APIs

Expertise in Amazon Web Services, particularly in data-centric services such as Redshift, S3, and Glue

Solid proficiency in Apache Airflow and Apache Spark, utilizing them for data processing and pipeline automation

Fluency in Python and SQL for data processing purposes

Experience with Databricks and PySpark for pipeline automation

Familiarity with CI/CD tools to facilitate the efficient delivery of data solutions

Robust analytical skills, enabling effective problem-solving and decision-making in complex data environments

Capability to communicate technical concepts effectively to a non-technical audience

Advanced proficiency in the English language (Upper-Intermediate level), facilitating clear written and spoken collaboration in team meetings and discussions with stakeholders

Hands-on experience with Redshift for data warehousing and management