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Why this grade This listing scored 39/100, which is an F. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
-10 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Key Responsibilities
- ETL Data Engineering: Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines, to ensure efficient data extractions, transformation, and loading.
- Data Warehousing: Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SWL Pool.
- Data Source Expertise: Extract data from various sources, including REST APIs, SWL database tables, and CSV files.
- Azure Synapse Analytics Expertise: Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance.
- Data Fabric Concepts: Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging, to enhance data management capabilities.
- Data Modeling: Collaborate with data architects to create data models and schemas that align with business requirements.
- Data Quality: Implement data quality checks and validation processes to maintain data accuracy and consistency.
- Performance Tuning: Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs.
- Monitoring and Troubleshooting: Monitoring ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability.
- Documentation: Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations.
- Collaboration: Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives.
- Security and Compliance: Ensure data security and compliance with data governance and privacy standards.
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience, with certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus.
- Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files.
- Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault.
- Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL to effectively extract, transform, and load data.
- Knowledge of data integration best practices and tools.
- Experience with version control systems, such as Git (Azure DevOps).
- Strong problem-solving and analytical skills, with a keen attention to detail.
- Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment with shifting priorities.
- Familiarity with big data technologies, machine learning, and data analysis preferred.
- Experience with data visualization tools (e.g. Power BI, Tableau) and Agile Methodologies a plus.
Company Benefits
- Competitive salary and bonuses, including performance-based salary increases.
- Generous paid-time-off policy
- Flexible working hours
- Work remotely
- Continuing education, training, conferences
- Company-sponsored coursework, exams, and certifications
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 09 Aug 2026 Himalayas first sighting
Seen on 1 board over 0 days.