Senior Data Engineer

As a Senior Data Engineer at Pattern, you will be involved in solving business problems that significantly impact the company's competitive edge. **Roles and Responsibilities:** - Develop, deploy, and support automated, scalable real-time and batch data streams from various sources into the lakehouse. - Implement data auditing strategies to ensure data quality, troubleshoot issues related to large-scale data processing workflows, and maintain data pipeline processes. - Collaborate with technology teams and partners to define data requirements and facilitate data access. - Optimize application and query performance utilizing profiling tools and SQL or other relevant query languages. - Translate business and analytics requirements into comprehensive data models and pipelines. - Foster data expertise and take ownership of data quality in assigned areas. - Collaborate with data infrastructure teams to address and resolve issues effectively. **Required Qualifications:** - Bachelor's Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, a related field, or equivalent professional experience. - 7+ years of overall experience. - 3+ years of experience with SQL and Python. - 3+ years of experience in building data pipelines using modern data architectures. - 2+ years of experience with data warehouses like Redshift, BigQuery, Snowflake, or similar. - Familiarity with open-source data architectures such as Spark, Hive, Trino/Presto, or similar. - Proficiency in software engineering and scripting. - Strong communication skills for effective cross-collaboration across data management and analytics domains. - Expertise in working with data systems dealing with massive data volumes from diverse sources. - Ability to lead a team of Data Engineers. **Preferred Qualifications:** - Experience with time series databases. - Advanced knowledge of SQL, including writing stored procedures, triggers, analytic/windowing functions, and query optimization. - Proficiency in Snowflake, including stream and task orchestration. - Background in Big Data, non-relational databases, Machine Learning, and Data Mining is advantageous. - Familiarity with cloud-based technologies like SNS, SQS, SES, S3, Lambda, and Glue. - Experience with modern data platforms such as Redshift, Cassandra, DynamoDB, Apache Airflow, Spark, or ElasticSearch. - Expertise in Data Quality and Data Governance. As a Senior Data Engineer at Pattern, you will be involved in solving business problems that significantly impact the company's competitive edge. **Roles and Responsibilities:** - Develop, deploy, and support automated, scalable real-time and batch data streams from various sources into the lakehouse. - Implement data auditing strategies to ensure data quality, troubleshoot issues related to large-scale data processing workflows, and maintain data pipeline processes. - Collaborate with technology teams and partners to define data requirements and facilitate data access. - Optimize application and query performance utilizing profiling tools and SQL or other relevant query languages. - Translate business and analytics requirements into comprehensive data models and pipelines. - Foster data expertise and take ownership of data quality in assigned areas. - Collaborate with data infrastructure teams to address and resolve issues effectively. **Required Qualifications:** - Bachelor's Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, a related field, or equivalent professional experience. - 7+ years of overall experience. - 3+ years of experience with SQL and Python. - 3+ years of experience in building data pipelines using modern data architectures. - 2+ years of experience with data warehouses like Redshift, BigQuery, Snowflake, or similar. - Familiarity with open-source data architectures such as Spark, Hive, Trino/Presto, or similar. - Proficiency in software engineering and scripting. - Strong communication skills for effective cross-collaboration across data management and analytics domains. - Expertise in working with data systems dealing with massive data volumes from diverse sources. - Ability to lead a team of Data Engineers. **Preferred Qualifications:** - Experience with time series databases. - Advanced knowledge of SQL, including writing stored procedures, triggers, analytic/windowing functions, and query optimization. - Proficiency in Snowflake, including stream and task orchestration. - Background in Big Data, non-relational databases, Machine Learning, and Data Mining is advantageous. - Familiarity with cloud-based technologies like SNS, SQS, SES, S3, Lambda, and Glue. - Experience with modern data platforms such as Redshift, Cassandra, DynamoDB, Apache Airflow, Spark, or ElasticSearch. - Expertise in Data Quality and Data Governance.