Senior Data Engineer Interview Preparation
Бюджет: $40.0 - $40.0
HOURLY / PART_TIME
⭐ 5.00 (2)
United States
hadoop, pyspark, aws-glue-etlservice, sql, sas, machine-learning, computer-networking, python, etl-pipelines, data-modeling
Preferred qualifications
- Experience: Intermediate
We are seeking an experienced Senior Data Engineer to assist with interview preparation. The ideal candidate will have a strong background in data engineering and be able to provide guidance on common interview questions and topics. The role involves helping the candidate prepare for a Senior Data Engineer position by focusing on key skills and areas of expertise.
The Role is below
About The Role
The Content Data Solutions team builds and maintains best in class data products enabling business teams to analyze and measure subscriber movements and support revenue generation initiatives. The Senior Data Engineer will contribute to the Company’s success by partnering with business, analytics and infrastructure teams to design and build data pipelines to facilitate measuring subscriber movements and metrics. Collaborating across disciplines, they will identify internal/external data sources, design table structure, define ETL strategy & automated Data Quality checks.
Responsibilities
Contribute to the design and growth of our Data Products and Data Warehouses around Content Performance data.
Design and develop scalable data warehousing solutions, building ETL pipelines in Big Data environments (cloud, on-prem, hybrid)
Our tech stack includes AWS, Databricks, Snowflake, Spark and Airflow
Help architect data solutions/frameworks and define data models for the underlying data warehouse and data marts
Collaborate with Data Product Managers, Data Architects and Data Engineers to design, implement, and deliver successful data solutions
Maintain detailed documentation of your work and changes to support data quality and data governance
Ensure high operational efficiency and quality of your solutions to meet SLAs and support commitment to our customers (Data Science, Data Analytics teams)
Be an active participant and advocate of agile/scrum practice to ensure health and process improvements for your team
Basic Qualifications
5+ years of data engineering experience developing large data pipelines.
Strong understanding of data modeling principles including Dimensional modeling, data normalization principles.
Experience using analytic SQL, working with traditional relational databases and/or distributed systems (Snowflake or Redshift), required.
Experience using programming languages (e.g. Python, Pyspark)
Good understanding of SQL Engines and able to conduct advanced performance tuning.
Ability to think strategically, analyze and interpret market and consumer information.
Strong communication skills – written and verbal presentations.
Comfortable working in a fast-paced and highly collaborative environment.
Preferred Qualifications
Experience with Snowflake, Databricks/EMR/Spark & Airflow a plus.
I need someone to help me clear this interview. I am decent with pyspark, sql, snowflake. I am not good with leetcode python, data modeling, system design. I need someone to help me understand those concepts do a mock interview and help me sharpen up the concepts also help me with the coding section.
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