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Data Engineer with Clickhouse

Talent Groups

Bellevue, Washington • Today

Easy Apply

Contract

Depends on Experience

Senior Software Engineer - Ad Intelligence Data Platform

Eliassen Group

Seattle, Washington • Today

Contract

Senior Data Engineer

JellyFish

Remote • Today

Full-time

USD 165,000.00 - 235,000.00 per year

Senior FDE Data Engineer (FedD140/FedD148)

Defense Unicorns

Remote • Today

Full-time

USD 148,750.00 - 201,250.00 per year

Job Details

Skills

Data Engineer
Azure
Clickhouse
Apache Hadoop
ADF
Databricks
HDFS
SQL
Python
Microsoft Azure

Summary

Job Description

Mandatory Primary Skills: Hadoop, Python, Databricks, Click house DB , ADLS, SQL + Azure cloud technologies above all with Azure (such as ADF, Databricks, Log Analytics, Logic App, Key Vault, Blob Storage, ADLS, etc.)

Secondary Skills: Snowflake ,

Detailed JD as below.

We run a near real-time analytics platform for mobile network data, ingesting billions of rows a day from Azure Data Lake/HDFS into Click House and serving subscriber-level queries back to internal APIs in tens of milliseconds. We are expanding the platform footprint to support additional use cases by adding more datasets
Data Engineer would work on: extending the Python ingestion framework that loads from Azure Data Lake/HDFS; table design covering partitioning, sort keys, TTL and materialized views; operational diagnosis of merge behaviour, part counts and replication lag; and integration with Snowflake and Databricks Iceberg alongside the primary feeds.
We need strong analytical SQL and experience with a columnar or MPP database — Click House, Big Query, Redshift or similar.
Python sufficient to own a production ingestion framework rather than write scripts.
Comfort at hundreds of billions of rows, since the failure modes differ from smaller systems.
Cloud object storage and Parquet. Enough Kubernetes to tell whether a problem is the database or the platform underneath it.
Strongly preferred: direct Click House experience, particularly Merge Tree engines and aggregate function states, and telecom data such as DNS , IPFIX, etc.
Click House specifically is uncommon, and we would rather have a strong engineer from an adjacent system than a weak one with the exact keyword.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91099677
Position Id: 9093055
Posted 2 hours ago

Fitment

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Anuradha Karod

Recruiter @ Talent Groups

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Project description The project focuses on designing and delivering scalable cloud-based data engineering solutions on Microsoft Azure. The role will support large-scale data integration, analytics, machine learning, AI solutions, and business intelligence through modern data platforms and automated ETL/ELT pipelines. Responsibilities Design, develop, and optimize ETL/ELT solutions using Azure Databricks, LakeBase, and Spark. Build and deploy large-scale data pipelines supporting analytics, mac

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Job Details

Skills

Data Engineer
Azure
Clickhouse
Apache Hadoop
ADF
Databricks
HDFS
SQL
Python
Microsoft Azure

Summary

Job Description

Secondary Skills: Snowflake ,

Detailed JD as below.

We run a near real-time analytics platform for mobile network data, ingesting billions of rows a day from Azure Data Lake/HDFS into Click House and serving subscriber-level queries back to internal APIs in tens of milliseconds. We are expanding the platform footprint to support additional use cases by adding more datasets
Data Engineer would work on: extending the Python ingestion framework that loads from Azure Data Lake/HDFS; table design covering partitioning, sort keys, TTL and materialized views; operational diagnosis of merge behaviour, part counts and replication lag; and integration with Snowflake and Databricks Iceberg alongside the primary feeds.
We need strong analytical SQL and experience with a columnar or MPP database — Click House, Big Query, Redshift or similar.
Python sufficient to own a production ingestion framework rather than write scripts.
Comfort at hundreds of billions of rows, since the failure modes differ from smaller systems.
Cloud object storage and Parquet. Enough Kubernetes to tell whether a problem is the database or the platform underneath it.
Strongly preferred: direct Click House experience, particularly Merge Tree engines and aggregate function states, and telecom data such as DNS , IPFIX, etc.
Click House specifically is uncommon, and we would rather have a strong engineer from an adjacent system than a weak one with the exact keyword.

Dice Id: 91099677
Position Id: 9093055
Posted 2 hours ago

Fitment

Dice Job Match Score™

To see how well you match this job, please log in or create an account.

Once logged in, be sure to complete your profile to get the most accurate match score.

Contact the job poster

Anuradha Karod

Recruiter @ Talent Groups

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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