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.

The candidate must have 5+ years of experience as an HR Data Engineer, demonstrating leadership in HR data engineering transformations and the implementation of data pipelines and solutions within the People Analytics/HR domain. A strong understanding of HR data, HR employee lifecycle processes (including talent acquisition, development, workforce planning, engagement, employee listening, and external benchmarking), and HCM data architecture, models, and pipelines is essential. Experience design…

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…

The Data Engineering Manager - Hands On role requires experience as a Data Manager with a strong focus on the technical side, previous experience in Startups and Fintechs, hands-on experience with setting up and scaling data infrastructure, proficiency in Python, SQL, and modern data tools like DBT, Snowflake, Fivetran, Hightouch, and other ETL/reverse ETL tools, and strong data engineering skills including data pipeline creation and maintenance.

Candidates should possess experience as a Data Engineer, including working with analysts and engineering teams, with expertise in data warehousing, ETL/ELT pipelines, and analytics infrastructure; strong SQL skills encompassing schema design, query optimization, and data model evolution; and experience with modern data stack tools such as Snowflake, dbt, and cloud platforms, preferably AWS, along with an ownership mindset and effective communication skills.

Candidates should have 5+ years of experience in database development, integration, and data analytics tools. A minimum of 5 years of experience designing and implementing complex Data Warehouse and Data Lake data models, specifically using the Kimball methodology, is required. Proficiency in managing ETL/ELT processes with large datasets and experience with columnar data structures are also necessary.

Candidates should possess a University degree in computer science, engineering, mathematics, or a related field, or equivalent experience. They should also have broad range of experience within large-scale Database and/or Data Warehouse technology, ETL, analytics and cloud technologies, hands-on expertise with SQL and SQL analytics, and outstanding presenting skills to both technical and executive audiences.

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 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…