Snowflake Data Engineer

@vishal1145

Your BI Quality Dashboard won't catch issues if you're only validating data at the reporting layer. Most data quality problems originate upstream - during ingestion or transformation - and by the time Power BI flags them, you've already delivered bad metrics to stakeholders. Before we scope this, I need clarity on two things: What's your current data lineage visibility in Snowflake? Can you trace a discrepancy back to the source table and transformation logic, or are you debugging blind? Second, are you running any automated data quality checks today (dbt tests, Great Expectations, custom SQL validators), or is this entirely manual investigation? Here's the approach: - SNOWFLAKE DATA QUALITY: Build automated validation queries using Snowflake streams and tasks to catch anomalies (null spikes, duplicate keys, referential integrity breaks) before they hit your BI layer, reducing firefighting by 70%. - SQL OPTIMIZATION: Rewrite your complex joins and aggregations using clustering keys and materialized views to cut query runtime from minutes to seconds, ensuring your dashboard refreshes don't timeout. - POWER BI QA DASHBOARD: Design a monitoring layer that tracks data freshness, row count deltas, and schema drift across critical tables, giving stewards real-time alerts instead of post-mortem reports. - DATA GOVERNANCE FRAMEWORK: Implement role-based access controls and data classification tags in Snowflake to ensure compliance teams can audit who touched what data and when. I've built similar quality monitoring systems for 4 clients running multi-terabyte Snowflake environments, including one healthcare company where we reduced data incident tickets by 60% in 90 days. Let's schedule a 15-minute call to walk through your current architecture - I don't take on engagements where the root cause analysis process isn't clearly defined.

@sankargan88

Dear Client, I have prior experience on supporting engineers on SQL, Power BI, snowflake and many other things. Ping me to start discussing on further steps.

@KelvemFerreira

I have solid experience in data engineering, BI and automation, working with large volumes of data in cloud environments (AWS S3, Redshift, Athena) and development of scalable pipelines. Although my main focus was AWS, I have a strong domain in advanced SQL (complex queries and optimization) and rapid adaptation to new technologies such as Snowflake. I worked directly on the identification and resolution of data inconsistencies, in addition to building dashboards in Power BI for generation of strategic insights and quality monitoring. I also have experience collaborating with multidisciplinary teams in agile environments and using tools such as Jira. I can support the creation of QA dashboards, proactive monitoring and implementation of good data governance practices. Availability: 1–2h/day (early morning or evening) Rate: €20/hour Relevant experience: projects with data analysis, automation and large-scale BI

@ravikumarsingh1

This is exactly the kind of work where Snowflake + data quality + BI need to be aligned, not handled separately. I focus on identifying root causes—not just fixing symptoms. Relevant experience: Snowflake: query optimization, data validation, troubleshooting pipeline issues SQL: complex joins, window functions, performance tuning Power BI: building QA dashboards, KPI tracking, anomaly detection Data quality: reconciliation checks, null/duplicate detection, schema validation Worked with cross-functional teams (data, business, reporting) How I’ll support: Identify and trace data discrepancies at source → transformation → reporting Build/assist with BI QA dashboard (data freshness, accuracy, alerts) Implement data quality checks (row counts, thresholds, variance tracking) Support Jira-based tracking and resolution workflow Availability: 1–2 hours/day Immediate start Hourly rate: 1000/hour I focus on making data reliable and explainable, not just “fixed.”

@GelsonVitorino2

Hello! I am a professional with experience in advanced SQL, data analysis, and dashboard development in Power BI. I am capable of investigating data inconsistencies, optimizing queries, and supporting data validation and quality processes. I have experience working with data in analytical environments and collaborating with technical and business teams to solve end-to-end problems. I have strong attention to detail, good communication skills, and experience in providing ongoing support for data projects. I am available to work daily (1-2 hours), with flexible hours and immediate start.

@abdelrahman5129

Hello, I’m a Data Engineer with strong hands-on experience in Snowflake, data pipelines, and BI solutions, and I can effectively support your data quality and BI initiatives. I’ve worked on end-to-end data workflows including ETL, data warehousing, and data validation, with a strong focus on identifying and resolving data quality issues. In Snowflake, I handle complex transformations, query optimization, and troubleshooting discrepancies across large datasets. I have advanced SQL skills and experience building Power BI dashboards, including QA dashboards for monitoring data integrity and detecting anomalies proactively. I’ve also collaborated closely with data stewards and reporting teams to ensure accurate and reliable data. Additionally, I’m familiar with data governance concepts, validation rules, and monitoring processes, and I use tools like Jira for tracking and managing tasks efficiently. I’m ready to start immediately and contribute to improving your data quality and BI processes. Best regards, Abdelrahman Mohamed

@maiksferreira

Currently, I work as an Analytics Engineer in a Latin America (LatAm) team focused on data engineering and analytics for the agricultural sector, collaborating with multicultural teams and supporting operations. I have strong technical knowledge in data manipulation tools, logical structures, and problem-solving. My role in the team is centered on developing and maintaining pipelines with a focus on flow optimization, data modeling, documentation, and ensuring the quality and consistency of our databases and my main techs are snowflake, power bi, SQL language and also quality assurance process.

@BharathReddy1980

Hi, I’m very interested in this opportunity and available to start immediately. Snowflake Experience (Mandatory): I have hands-on experience working with Snowflake for data warehousing, including data modeling, ETL/ELT pipeline development, performance optimization, and writing complex SQL queries. I’ve worked on integrating Snowflake with tools like Airflow/dbt and building scalable data pipelines. Data Quality / BI Work: - Implemented data validation and quality checks to ensure consistency and accuracy across datasets - Built dashboards and reports using BI tools (such as Power BI/Tableau) to support business decision-making - Experience in transforming raw data into actionable insights through clean data models Have a discussion regarding the Hourly rate and daily avalibility

@RahulTheAnalyst

As an experienced Snowflake data engineer and BI consultant, I am confident that my skills and insights could be a great asset in resolving the data quality issues your client currently faces. My primary focus on Snowflake combined with my advanced SQL and Power BI proficiency aligns perfectly with the responsibilities outlined in your project. Throughout my career, I've worked extensively in building data-driven solutions and BI Quality Assurance Dashboards, a skill that will prove invaluable in enabling proactive monitoring of data integrity for your client. Lastly, my analytical thinking and technical proficiency combined with my dedication to regulatory compliance makes me an ideal fit for ensuring smooth operations within your large scale-data environments. I am excited about the opportunity to contribute to your project as this kind of role really excites me - delving into granular layers of data, finding patterns and resolving issues is real challenging and satisfying

@farazs48

With my specialized focus on Snowflake, a thorough understanding of data governance, and proficiency in Power BI, I am ideally positioned to support your client's data quality and BI initiatives. My extensive experience in identifying and troubleshooting data quality issues within Snowflake, combined with my skill in generating advanced SQL queries for optimization purposes, make me the perfect candidate for your project. Additionally, I have a strong familiarity with Jira and other similar tools that further enhance my ability to collaborate effectively with business data stewards, data engineering, and reporting teams. My comprehensive grasp of Data Governance and data quality frameworks will greatly assist in developing a robust BI Quality Assurance Dashboard for proactive monitoring of data integrity. I can offer you flexibility in terms of availability during early mornings or late evenings to accommodate your needs. My data recovery background also equips me with problem-solving skills that go beyond just identifying issues; I am adept at supporting end-to-end resolution. I am ready to delve into your Snowflake project right away, and my competitive hourly rate is proportionate to the value I can bring to your team. Look no further; let's get started on optimizing your data quality processes!