Senior Data & Analytics Engineer

Ycotek; Minneapolis (MN); On-site; USD 120,000 - 180,000; Full time

Job summary

Ycotek is seeking a Sr. Data & Analytics Engineer to join our dynamic team. You will design, develop, and optimize data pipelines and ETL processes across multiple sources to enable scalable analytics.

You will collaborate with business stakeholders, data analysts and data scientists to deliver actionable insights, build data warehouses and governance practices, and mentor junior engineers while advancing data architecture at scale.

Qualifications

• 4+ years of experience in data engineering or a related field.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’s preferred).
• Strong experience with SQL and Python.
• Experience with data warehousing technologies and ETL tools.
• Ability to translate business needs into technical solutions.
• Excellent verbal and written communication skills.

Responsibilities

• Design, develop, and optimize data pipelines and ETL processes for data ingestion, transformation, and integration from multiple sources.
• Manage and maintain data warehouses and data lakes, ensuring accuracy, availability, and security.
• Work closely with business stakeholders, data analysts, and data scientists to translate business needs into technical solutions.
• Implement data quality frameworks, monitoring systems, and performance tuning.
• Contribute to data modeling, architecture, and governance best practices.
• Support the development of dashboards, reports, and analytical models to provide actionable insights.
• Mentor junior engineers and foster a culture of collaboration and technical excellence within the data team.

Skills

SQL

Python

Data warehousing

ETL tools

Airflow

Tableau

Power BI

Looker

Cloud platforms

Hadoop

Spark

Kafka

Data modeling

Governance

Communication

Bachelor's degree

Master's preferred

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field

Master’s degree preferred

Tools

Snowflake

Redshift

BigQuery

Apache Airflow

Talend

Fivetran

Job description

We are looking for a self-driven, motivated, and results-oriented professional to join our dynamic team as a Sr. Data & Analytics Engineer. Please find the role details below;

Key Responsibilities

• Design, develop, andoptimizedata pipelines and ETL processes for efficient data ingestion, transformation, and integration from multiple sources.
• Manage andmaintaindata warehouses and data lakes, ensuring accuracy, availability, and security.
• Work closely with business stakeholders, data analysts, and data scientists to translate business needs into technical solutions.
• Implement data quality frameworks,monitoringsystems, and performance tuning.
• Contribute to data modeling, architecture, and governance best practices.
• Support the development of dashboards, reports, and analytical models toprovideactionable insights.
• Mentor junior engineers and foster a culture of collaboration and technical excellence within the data team.

Key Specifications

• Strong experience in SQL, Python.Familiarity with data warehousing technologies (e.g., Snowflake, Redshift,BigQuery) and ETL tools (e.g., Apache Airflow, Talend,Fivetran).
• Experience with data visualization tools such as Tableau, Power BI, or Looker.
• Knowledge of cloud-based platforms (AWS, Google Cloud, Azure) and associated data services.
• Experience with Hadoop, Spark, Kafka, or other big data technologies is a plus.
• Strong understanding of relational databases, data modeling concepts, and designing data architectures.
• Ability to analyze complex data sets andidentifytrends, correlations, and insights.
• Excellent verbal and written communication skills, with the ability to explain complex data concepts to non-technical stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (Master’spreferred).
• 4+ years of experience in data engineering or a related field, preferably in analytics or business intelligence.
• Strong experience working with large datasets and complex data pipelines.
• Previousexperience in a similar industry or field is a plus.

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