Remote Data Engineer Jobs

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 a proven track record of designing and building scalable data platforms, including data warehouses, pipelines, and data lakes. Experience with ETL/ELT processes using tools like SQL and dbt is essential, as is the ability to create effective data models for analytics and reporting. Familiarity with business intelligence tools such as Tableau and a strong understanding of data governance and quality standards are required. The role also necessitates cross-functional collabo…

Candidates should have 3+ years of professional data engineering experience, including proficiency in SQL, Python, DBT, Kafka, and Gitlab. Experience with relational databases, strong attention to detail, analytical capabilities, and comfort with the Unix/Linux command line are also required. An undergraduate degree in Computer Science is necessary, and experience with cloud data warehouses like Snowflake, Redshift, or BigQuery, and creating data visualizations is highly valued.

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 must have a Bachelor's degree in Business, Economics, Statistics, or Computer Science and at least 5 years of experience in a data analytics or data engineering role, preferably in a SaaS business. High proficiency in SQL is mandatory, along with existing experience with Databricks. Python experience (especially with data processing libraries like Pandas/Polars) and/or data streaming technologies (Kafka, Spark Streaming), experience with data modeling frameworks (especially dbt Cloud)…

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 possess a degree in Computer Science, Engineering, or a related field, with at least 3 years of technical leadership and engineering management experience, preferably in a startup environment. A minimum of 10 years of experience in data engineering is required, including building and maintaining production pipelines and distributed computing frameworks. Strong expertise in Python, Spark, SQL, and Airflow is essential, along with hands-on experience in pipeline architecture, cod…

Candidates must possess a BS/BA degree in Mathematics, Computer Science, or a related STEM field, with a minimum of 5 years of demonstrated experience writing production-level code in Python and SQL, preferably MySQL. Experience with Airflow, Kubernetes, building end-to-end ETL pipelines, utilizing REST APIs, and version control (git) is required. Proficiency in continuous integration and deployment, shell scripting, cloud computing infrastructures (AWS), web scraping, cleaning unstructured data…

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

Candidates should have 3+ years of experience as a Data Engineer with a strong focus on data pipeline development and data warehousing, possessing hands-on experience with data modeling, cloud data warehouses, Python, SQL, data ingestion tools, ETL/ELT processes, and Airflow. Experience with Terraform, DBT, Snowflake, and Meltano is considered a plus.