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 have 5+ years of experience in Data Analytics and/or Data Engineering, with proven experience implementing ETL/ELT processes. Strong proficiency in SQL is required, along with experience using dbt for transformation stages and working with cloud data warehouses like Snowflake, BigQuery, or Redshift. Hands-on experience in data modeling, schema design, and optimization techniques is essential. Proven experience maintaining data transformation pipelines, ensuring data availabilit…

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 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 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 over 7 years of experience in data engineering, including at least 2 years in a team lead or management role with a proven track record in recruiting, developing, and mentoring high-performing teams. Experience with DevOps principles, monitoring, automation for data infrastructure, and deep knowledge of data modeling techniques and programming fundamentals (e.g., Python) are required. Hands-on expertise with SQL and modern data tools such as Snowflake, dbt, and Spark is ne…

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 should have experience building and maintaining dbt data models within a medallion architecture, transforming staging data into intermediate and mart layers. Proficiency in writing production-quality SQL transformations in Snowflake and implementing data validation and testing using dbt tests is required. Experience with BI tools like QuickSight and a background in healthcare technology are preferred.

Candidates must possess a Bachelor's degree and 2-5 years of technical experience in data analysis. Required skills include proficiency in SQL, comprehensive knowledge of Microsoft Office Applications, expertise in assessing large complex data sets and performing root cause analysis, and experience with Power BI or similar tools. A passion for improving consumer experiences is also essential. Preferred qualifications include an advanced degree in a quantitative discipline, experience with Snowfl…

Candidates should possess a Bachelor’s degree in Computer Science, Engineering, or a related field, and have at least 5 years of experience as a Data Engineer. Strong experience with data warehousing, ETL processes, and data modeling is required, along with proficiency in SQL and Python. Experience with cloud platforms such as AWS, Azure, or GCP is preferred.

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.