We are looking for a Senior Data Engineer to design, build, and optimize scalable data platforms that support analytics, ecommerce, logistics, and marketing initiatives. This role will be responsible for developing robust data pipelines, improving the data infrastructure, and ensuring high-quality, reliable data solutions in an AWS environment. The ideal candidate has strong expertise in Python, SQL, Spark, Airflow, and cloud-based data architectures, along with excellent communication skills and a collaborative mindset.

Responsibilities

• Design, build, and maintain scalable data pipelines for analytics, ecommerce, logistics, and marketing.
• Improve and maintain the company’s data infrastructure and tooling, including Redshift/Snowflake, Airflow, and Fivetran.
• Architect data processing systems capable of handling complex data flows and large-scale datasets.
• Develop reliable, efficient, and cost-effective data solutions in an AWS environment.
• Ensure high standards of data quality through automation and best engineering practices.
• Optimize platform performance, resiliency, scalability, and operational costs.
• Collaborate closely with software engineers, analysts, and business stakeholders.
• Mentor engineers and analysts on data engineering best practices.
• Participate in architecture discussions and technical decision-making.

Must Have

• 4+ years of experience as a Data Engineer working with modern data technologies.
• Strong proficiency in Python and SQL.
• Experience processing large-scale datasets.
• Hands-on experience with Apache Spark and Apache Airflow.
• Experience designing and architecting data processing systems in AWS.
• Experience with Redshift and/or Snowflake.
• Knowledge of Fivetran or similar data ingestion tools.
• Strong understanding of data quality, automation, and data engineering best practices.
• Excellent communication and interpersonal skills.
  Nice to Have
• Experience with streaming technologies such as Kafka or AWS Kinesis Firehose.
• Knowledge of Docker and/or Kubernetes.
• Familiarity with Ruby or R.
• Experience building or migrating a Data Warehouse.
• Experience leading projects or mentoring technical teams.

We are looking for a Senior Data Engineer to design, build, and optimize scalable data platforms that support analytics, ecommerce, logistics, and marketing initiatives. This role will be responsible for developing robust data pipelines, improving the data infrastructure, and ensuring high-quality, reliable data solutions in an AWS environment. The ideal candidate has strong expertise in Python, SQL, Spark, Airflow, and cloud-based data architectures, along with excellent communication skills and a collaborative mindset.

Responsibilities

• Design, build, and maintain scalable data pipelines for analytics, ecommerce, logistics, and marketing.
• Improve and maintain the company’s data infrastructure and tooling, including Redshift/Snowflake, Airflow, and Fivetran.
• Architect data processing systems capable of handling complex data flows and large-scale datasets.
• Develop reliable, efficient, and cost-effective data solutions in an AWS environment.
• Ensure high standards of data quality through automation and best engineering practices.
• Optimize platform performance, resiliency, scalability, and operational costs.
• Collaborate closely with software engineers, analysts, and business stakeholders.
• Mentor engineers and analysts on data engineering best practices.
• Participate in architecture discussions and technical decision-making.

Must Have

• 4+ years of experience as a Data Engineer working with modern data technologies.
• Strong proficiency in Python and SQL.
• Experience processing large-scale datasets.
• Hands-on experience with Apache Spark and Apache Airflow.
• Experience designing and architecting data processing systems in AWS.
• Experience with Redshift and/or Snowflake.
• Knowledge of Fivetran or similar data ingestion tools.
• Strong understanding of data quality, automation, and data engineering best practices.
• Excellent communication and interpersonal skills.
  Nice to Have
• Experience with streaming technologies such as Kafka or AWS Kinesis Firehose.
• Knowledge of Docker and/or Kubernetes.
• Familiarity with Ruby or R.
• Experience building or migrating a Data Warehouse.
• Experience leading projects or mentoring technical teams.