Data Engineer

Role Overview:

• You will analyze large volumes of business data, solve real-world problems, and develop metrics and business cases that enable actionable insights. You will leverage data from platforms such as Jira, internal portals, and Salesforce, working with Product Managers, Software Engineers, Data Scientists, and Business Intelligence Engineers to automate analysis and scale data usage across the organization. You will own and support key datasets, build and optimize data pipelines, and contribute to modern data warehousing, reporting, and analytics. You’ll work extensively in AWS and modern data tooling, writing advanced SQL and Python to deliver reliable, high-performance, and cost-efficient data solutions.
• Responsibilities:
• Design, implement, and support analytical data infrastructure with knowledge of modern data warehouse concepts
• Build, maintain, and optimize scalable data pipelines and ETL processes for structured and unstructured data
• Optimize data storage and retrieval for performance, scalability, and cost efficiency
• Manage and support AWS resources and services including EC2, S3, Glue, Lambda, APIs, IAM, CloudWatch, and CloudTrail
• Collaborate with other teams to extract, transform, and load data from diverse sources using SQL and AWS big data technologies
• Explore and adopt emerging AWS capabilities to improve platform efficiency and unlock new data and analytics use cases
• Work with Data Scientists and Business Intelligence Engineers to adopt best practices in reporting and analysis
• Automate workflows and enable self-service reporting for internal users
• Maintain internal reporting tools, troubleshoot issues, and develop enhancements
• Gather requirements and translate them into report specifications and deliverables
• Work with engineering teams to shape and implement BI infrastructure including data warehousing, reporting, and analytics platforms
• Write advanced SQL queries and Python code to develop operational solutions
• Work with Snowflake and related data patterns as needed
• Collaborate across teams to align AI initiatives with organizational goals; demonstrate working knowledge of AI concepts
• Support CI/CD pipelines and participate in deployments
• Required Qualifications:
• Bachelor’s degree in Computer Science, Information Technology, or a related field
• 3–5 years of experience in data engineering (or related role) with a track record of delivering data solutions
• Strong experience with AWS services including Glue, Lambda, S3, EC2, CloudWatch, and CloudTrail
• Experience with dbt, Snowflake, SQL, Python, and Qlik
• Proficient in SQL, including complex query writing, optimization, and performance tuning
• Experience with NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB) and understanding use cases
• Strong programming skills in Python, Java, or Scala; experience with data processing frameworks such as Apache Spark and/or Hadoop
• Experience with cloud platforms (AWS, Azure, GCP) and data services such as Redshift, Azure Synapse, or BigQuery
• Knowledge of big data technologies such as Hadoop, Spark, Kafka, and HBase; experience with distributed data processing
• Familiarity with data orchestration tools such as Apache Airflow
• Experience with data versioning/testing tools such as DVC and dbt
• Understanding of data security practices including encryption, access controls, and data masking