Candidates should have at least 3 years of experience in analytics engineering, data engineering, or data analysis with a strong focus on building data pipelines and deriving insights. Advanced SQL skills for complex queries and performance optimization on large datasets are required. Experience with ELT/ETL and orchestration tools like Airflow is necessary, along with a solid foundation in data modeling principles. Candidates should possess strong problem-solving skills, attention to detail, an…

Candidates should possess 4+ years of experience as a Data Engineer, Analytics Engineer, or similar role with significant experience building and maintaining production data pipelines. Expert proficiency in SQL for complex data transformations, performance optimization, and working with large datasets is required, along with strong PostgreSQL experience being highly preferred. Proficiency in Python or another programming language for data pipeline development, automation, and scripting is also n…

Candidates should possess skills in Data & Tech, Engineering, Data & Analytics, Infrastructure & IT, Sales, Account Management, Field Services & Customer Support, Inside Sales, Outside Sales, and Creative & Marketing.

Candidates should have 3+ years of professional experience writing production-ready code in Python, DBT, Scala, or Java, with high proficiency in SQL and the ability to write efficient code considering resource and performance constraints. A minimum of 2 years of professional experience working directly with data pipelines, ideally with exposure to loan datasets, is required. Familiarity with relational data concepts, big data tools, and cloud-native technologies like Google Cloud Platform (BigQ…

Candidates should have over 7 years of data engineering experience in the relevant industry. Expertise in Data Warehousing platforms such as AWS RedShift or Snowflake and data lake/lakehouse architectures is required. Experience with Data Streaming platforms like AWS Kinesis or Firehose is essential. Candidates must demonstrate the ability to solve complex architectural problems and possess effective communication skills to translate technical designs into business representations. Proficiency i…

Candidates should possess 6-10 years of full-time experience in Data Analysis and/or Software Development, along with experience in data warehousing technologies such as SQL and NoSQL databases. Strong experience with reporting and analytics technologies is also required, as is a demonstrated ability to develop and maintain data-oriented web applications and scalable web services.

Candidates should possess expert-level proficiency in SQL and modern data stack technologies, with hands-on experience in Snowflake or similar data warehousing tools, including multi-cluster warehouse configuration and optimization. A strong background in CDC solutions and real-time data streaming (Kafka, Confluent), experience with both SQL and NoSQL databases (Postgres, MongoDB), and a proven track record of building ETL/ELT pipelines processing terabytes of data daily are essential. Understan…

Candidates should have 5+ years of experience analyzing large datasets, with strong forecasting experience using methodologies like ARIMA and Prophet for LTV and CAC. Fluency in SQL and statistical programming languages such as Python or R is required, along with experience building scalable data pipelines and ETL processes using DBT. Familiarity with analytical models supporting product teams and the ability to work independently with Finance are also necessary. Strong organizational and commun…

Candidates should possess 5-7 years of experience with cloud data warehouses, including at least 3 years of hands-on experience with Snowflake. A minimum of 4 years in data engineering, analytics engineering, or a similar data-focused role is required, along with a strong understanding of data warehousing concepts like Star/Snowflake schemas, slowly changing dimensions, and data marts. Proficiency in SQL, including advanced joins, CTEs, and window functions, is essential, as is experience with P…

The ideal candidate will have expertise in architecting, building, and maintaining scalable data ingestion infrastructure and operational systems. This includes proficiency in the 'EL' (Extract-Load) portion of an ELT stack, building robust, configuration-driven systems and event-driven processes that scale effectively for large enterprise datasets. Experience with scalable, incremental data migration from sources like RDS and DynamoDB into Snowflake, utilizing tools such as Kinesis, Airbyte, or…

Candidates must possess a minimum of 8 years of industry experience in data infrastructure/data engineering, with at least 8 years of experience in Python and SQL, and 4 years of experience with DBT, Snowflake, and Infrastructure as Code tools like CDK and Terraform. Familiarity with AWS services such as Lambda, Step Functions, Glue, RDS, EKS, DMS, and EMR is required, along with experience in big data platforms like Kafka, Hadoop, Hive, Spark, Cassandra, and Airflow. Experience with relational …

Candidates must possess a minimum of 5 years of experience working with high-volume data infrastructure and have experience with Databricks, AWS, ETL, and job orchestration.

Candidates must be experts in SQL and Python, possess at least 2 years of experience as a data engineer and 4 years of total software engineering experience, and be proficient in at least one additional core data engineering language like Scala, Java, or Rust. Experience with modern orchestration tools such as Airflow, Dagster, or Prefect, and a bias for action with effective prioritization skills are also required. Experience developing and scaling dbt projects, working in a SaaS or high-growth…

Candidates should possess a minimum of 5 years of experience working with high volume data infrastructure, demonstrating a strong engineering background and a desire to take ownership of data systems, with a focus on scalability and maintainability. Experience with data processing, storage, and ETL pipelines is essential, along with the ability to design and implement data models to meet business needs.

Candidates should possess a minimum of 6 years of industry experience in data infrastructure or data engineering, with a minimum of 6 years of experience utilizing Python and SQL, and at least 3 years of experience with DBT and Snowflake. Experience with AWS services such as Lambda, Step Functions, Glue, RDS, EKS, DMS, EMR, and familiarity with big data platforms like Snowflake, Kafka, Hadoop, Hive, Spark, Cassandra, Airflow, and experience with relational and NoSQL databases is required. Strong…