The Big Data Consultant is responsible for helping DesignMind clients design and implement large scale data analytics systems, and is involved in all phases of big data projects. The successful candidate must demonstrate a clear understanding of big data related technologies, methodologies and best practices and a proven ability to design big data solutions and develop code, scripts and data pipelines using modern on-premise and cloud tools.
When not busy with clients’ engagements, the Big Data Consultant is actively involved in building the DesignMind Big Data and Data Science practice products and services to integrate with existing practice offerings. If selected, you can expect challenging and exciting client engagements in the SF Bay Area and occasionally in other areas of the West Coast.
DesignMind offers Medical, Dental & Vision benefits, 401(k), performance bonuses, sunny offices in the heart of downtown San Francisco, and many other great perks.
- Bachelor's or Master’s degree in Computer Science or related fields (equivalent work experience considered).
- 2 years minimum experience working with the Hadoop ecosystem (Hadoop, Spark, Pig, Hive, etc.) in either on-premise or cloud environments (AWS, Azure).
- Significant experience programming in Python, Java or Scala.
- Experience with SQL and relational database programming.
- Experience with NoSQL databases (e.g., HBase, Cassandra, Mongo DB).
- Strong analytical skills.
- Creative problem solver.
- Eager to learn and apply new technologies.
- Excellent verbal and written communication skills.
- Strong team player capable of working in a demanding environment.
- High energy level; be self- motivated, with a results oriented demeanor.
- Prior experience with data warehousing and business intelligence systems.
- Agile development methodology.
- Experience working with customers (consulting experience a plus).
- Linux expertise.
- Python or R background for statistical modeling.
- Familiarity with current data science tooling.
- Background including mathematics, statistics, machine learning and data mining.
We look forward to hearing from you.