Biztec Global LLC
Responsibilities
Contribute to the design and growth of data products and systems supporting analytics and audience engagement initiatives.
Design and develop scalable data warehousing solutions, building ETL pipelines in Big Data environments (cloud, on-prem, hybrid).
Work with a tech stack that includes Hadoop, AWS, Snowflake, Spark, and Airflow; languages include Python and Scala.
Help architect data solutions/frameworks and define data models for the underlying data warehouse and data marts.
Collaborate with Data Product Managers, Data Architects, and Data Engineers to design, implement, and deliver data solutions.
Maintain detailed documentation to support data quality and governance.
Ensure high operational efficiency and quality of solutions to meet SLAs and support internal customers (Data Science, Data Analytics teams).
Actively participate in agile/scrum practices to ensure team health and continuous improvement.
Basic Qualifications
6+ years of data engineering experience developing large-scale data pipelines.
Strong SQL skills with the ability to create queries to extract and build performant datasets.
Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark).
Strong programming skills in Python, Scala, or Java.
Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, BigQuery).
Solid experience with data integration tools (e.g., Airflow) and maintaining data pipelines.
Strong background in data modeling techniques and data warehousing best practices.
Familiarity with Scrum and Agile methodologies.
Problem-solving mindset with strong attention to detail, analytical skills, and communication abilities.
Nice-to-have: experience with cloud technologies such as AWS (S3, EMR, EC2).
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Contribute to the design and growth of data products and systems supporting analytics and audience engagement initiatives.
Design and develop scalable data warehousing solutions, building ETL pipelines in Big Data environments (cloud, on-prem, hybrid).
Work with a tech stack that includes Hadoop, AWS, Snowflake, Spark, and Airflow; languages include Python and Scala.
Help architect data solutions/frameworks and define data models for the underlying data warehouse and data marts.
Collaborate with Data Product Managers, Data Architects, and Data Engineers to design, implement, and deliver data solutions.
Maintain detailed documentation to support data quality and governance.
Ensure high operational efficiency and quality of solutions to meet SLAs and support internal customers (Data Science, Data Analytics teams).
Actively participate in agile/scrum practices to ensure team health and continuous improvement.
Basic Qualifications
6+ years of data engineering experience developing large-scale data pipelines.
Strong SQL skills with the ability to create queries to extract and build performant datasets.
Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark).
Strong programming skills in Python, Scala, or Java.
Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, BigQuery).
Solid experience with data integration tools (e.g., Airflow) and maintaining data pipelines.
Strong background in data modeling techniques and data warehousing best practices.
Familiarity with Scrum and Agile methodologies.
Problem-solving mindset with strong attention to detail, analytical skills, and communication abilities.
Nice-to-have: experience with cloud technologies such as AWS (S3, EMR, EC2).
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