Big Data Engineer
A Big Data Engineer develops systems and infrastructure capable of handling large volumes of data, and uses complex analytical methods to derive insights and support decision-making.
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Sample Job Descriptions for Big Data Engineer
Below are the some sample job descriptions for the different experience levels, where you can find the summary of the role, required skills, qualifications, and responsibilities.
Junior (0-2 years of experience)
Summary of the Role
As a Junior Big Data Engineer, you will work alongside a team of skilled data professionals to manage large-scale data processing systems and databases. Your role will involve the collection, storing, processing, and analyzing of huge sets of data. This entry-level position is a great opportunity to develop a strong foundation in big data technologies and practices.
Required Skills
- Strong problem-solving skills with an emphasis on product development.
- Experience using statistical computer languages such as Python, SQL, etc., to process data.
- Experience with data visualization tools.
- Basic understanding of machine learning techniques and algorithms.
- Good communication and collaboration skills.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related field.
- Familiarity with big data tools such as Hadoop, Spark, Kafka, etc.
- Knowledge of various ETL techniques and frameworks.
- Understanding of SQL and NoSQL databases, including Postgres and Cassandra.
- Excellent analytical skills and the ability to work with large data sets to extract business insights.
Responsibilities
- Assist in the design, construction, and maintenance of scalable data pipelines.
- Implement complex, large-scale data sets that meet functional and non-functional business requirements.
- Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, etc.
- Work with stakeholders including data, design, product, and executive teams to support data-related technical issues and support their data infrastructure needs.
- Collaborate with data scientists and architects on data initiatives and ensure optimal data delivery architecture is consistent throughout projects.
Intermediate (2-5 years of experience)
Summary of the Role
As a Big Data Engineer, you will be responsible for developing, maintaining, evaluating, and testing big data solutions. You are expected to have a deep understanding of the big data technology landscape and possess the technical acumen to engineer solutions for data-driven decision making.
Required Skills
- Proficient in programming languages such as Java, Scala, or Python
- Ability to work in a Linux environment
- Skills in using cloud services like AWS, Azure, or GCP for big data tasks
- Familiarity with machine learning algorithms and data modeling is a plus
- Strong problem-solving skills and the ability to work under tight deadlines
- Excellent verbal and written communication skills
- Team player with a strong desire to be part of a highly productive and rapidly growing technology team
Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field
- At least 2 years of experience in a big data engineering role
- Experience with big data technologies such as Hadoop, Spark, Kafka, etc.
- Experience with building and optimizing data pipelines, architectures and data sets
- Strong analytic skills related to working with unstructured datasets
- Working knowledge of message queuing, stream processing, and highly scalable data stores
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra
- Experience with data pipeline and workflow management tools such as Azkaban, Luigi, Airflow, etc.
Responsibilities
- Design and implement scalable big data architecture
- Develop and maintain data pipelines for large-scale data processing
- Ensure data quality and reliability throughout pipelines
- Work closely with data scientists and analysts to provide the necessary data for analysis
- Optimize data retrieval, develop dashboards, and reports for various internal teams
- Stay current with new big data technologies and evaluate their potential to add value to the business
- Collaborate with cross-functional teams to resolve complex technical challenges
- Ensure compliance with data governance and security policies
Senior (5+ years of experience)
Summary of the Role
As a Senior Big Data Engineer, you'll lead the design and development of large-scale data processing systems and provide technical leadership within the data team. You're expected to have an extensive background in software engineering, data warehousing, and big data processing technologies. Your role involves optimizing data pipelines, building the infrastructure for optimal extraction, transformation, and loading of data from various sources, and ensuring that the architecture supports the company's needs both today and in the future.
Required Skills
- Expertise in programming languages such as Java, Scala, or Python.
- In-depth knowledge of big data processing technologies like Apache Spark and Hadoop ecosystem.
- Strong experience with NoSQL databases, such as Cassandra or MongoDB.
- Proficiency in building and optimizing 'big data' data pipelines, architectures, and data sets.
- Experience with stream-processing systems, such as Apache Storm or Samza.
- Ability to build processes that support data transformation, data structures, metadata, dependency, and workload management.
- Good understanding of distributed system design and architecture.
- Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Solid understanding of data security and data privacy practices.
- Excellent communication and leadership skills.
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- Minimum of 5 years' experience in a Big Data engineering role.
- Proven experience with big data tools such as Hadoop, Spark, Kafka, etc.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Strong understanding of SQL and experience with RDBMS.
- Experience with cloud services such as AWS, Azure, or Google Cloud Platform.
- Familiarity with machine learning algorithms and data science techniques.
- Proven ability to work with varied forms of data infrastructure, including relational databases, big data frameworks, and cloud platforms.
- Experience implementing data governance and privacy policies.
- Strong problem-solving skills and attention to detail.
Responsibilities
- Design and implement large-scale data processing systems.
- Develop and manage data warehouses and real-time processing solutions.
- Lead the architectural decisions and implementation of big data technologies.
- Work with cross-functional teams to identify and capture data needs of the organization.
- Ensure the performance, quality, and responsiveness of data systems.
- Mentor junior data engineers and review their work.
- Stay current with industry trends and introduce new technologies that can enhance data capabilities.
- Handle the extract, transform, load (ETL) process including data quality and consistency.
- Develop data APIs for data consumption by various internal and external stakeholders.
- Build analytics tools that provide actionable insights into key business metrics.
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