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We are seeking a talented Data Engineer with strong experience in Python, AWS, and Databricks to design and build scalable data pipelines and modern data platforms. The ideal candidate will help develop and maintain data infrastructure that supports analytics, machine learning, and business intelligence initiatives. This role requires hands-on experience working with large datasets, cloud-native architectures, and distributed data processing frameworks.
Job Responsibility:
Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Python and cloud technologies
Develop and optimize data solutions using AWS services and Databricks
Build and manage data lakes and data warehouses for structured and unstructured data
Implement data transformation and processing pipelines using Apache Spark within Databricks
Integrate data from multiple sources including APIs, databases, and streaming systems
Ensure data quality, governance, security, and compliance across the data platform
Monitor pipeline performance and troubleshoot data pipeline failures or latency issues
Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable datasets
Optimize storage and compute costs within the AWS ecosystem
Requirements:
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field
3+ years of experience in data engineering or data platform development
Strong programming experience with Python for data processing and automation
Hands-on experience with AWS cloud services such as: Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon EMR
Experience working with Databricks and Apache Spark for large-scale data processing
Strong knowledge of SQL and relational databases
Experience designing and maintaining ETL/ELT pipelines
Nice to have:
Experience with data orchestration tools such as Airflow or AWS Step Functions
Familiarity with streaming data technologies (Kafka, Kinesis, or Spark Streaming)
Experience with CI/CD pipelines and DevOps practices
Knowledge of data modeling, data warehousing, and lakehouse architectures
Experience working in Agile development environments