JD u2013 Data Engineering (ETL) Tech Lead
Experience & Expectations :
- Leverage extensive experience (8 to 12 years overall ETL experience, including 2u20133 years in a Technology Lead role & 4u20136 years in AWS) to drive solution design and delivery.
- We are seeking an experienced Tech Lead with strong expertise in Big Data (Spark, Cloudera).
- Experience orchestrating complex workflows using AWS Step Functions (state machines) for reliable and scalable data pipelines.
- Ability to design end-to-end serverless data architectures integrating Glue, Lambda, S3, and Redshift
- Candidates with exposure to drive / assist in architecture, development, and delivery of AI-powered data workflows, leveraging agent-based systems to automate data ingestion, transformation, validation, and orchestration along with modern AI paradigms (Agentic AI, LLMs) to design and lead next-generation intelligent data platforms and ETL pipelines will be preferred.
Core Responsibilities :
- Lead and manage the development team by helping them understand the requirements and provide technical guidance
- Design, build, and maintain high volume ETL/ELT pipelines across Hadoop (HDFS, Hive, Spark, Kafka) and AWS (Glue, EMR, Lambda, Step Functions, Redshift).
- Develop distributed data processing solutions using PySpark, Spark SQL, and scalable cloud serverless patterns.
- Implement reusable data ingestion frameworks for batch, ability to design & implement Orchestration process and Leverage AI
- Optimize data workflows using partitioning, bucketing, compression, file formats (Parquet/ORC).
- Understanding hybrid data lake architectures using S3 + HDFS, ensuring data governance and best practices are adheres
- To lead technical teams and deliver complex projects in an Agile environment
- Design and build the robust, scalable and secure software solutions across the having no/least adoption
- Define clear technical specifications and make architecture decisions that align with business goals and long-term scalability.
- Implement best practices (including secure code guidelines) through the implementation of unit tests, automation, leverage and code reviews. Drive continuous improvement in code quality and maintainability.
- Troubleshooting issues and proactively solving problems as they arise, ensuring the smooth operation of full stack applications
- Ability to understand the data flow diagram, data modelling and Lineages
- Job orchestration using Airflow, Control M, Step Functions, or event-driven triggers.
- Ensure data is protected and compliant with regulatory standards.
- Work closely with business stakeholders to enable high quality datasets.
- Provide technical support in architecture decisions, code reviews, and best practice adoption and provide technical guidance to peers/juniors in team.
- Own deployment, incident response, and post-incident reviews for production environments, troubleshooting Spark performance issues, job failures, and cluster bottlenecks.
- Optimize cost and usage of AWS resources and recommend architecture improvements.
- Collaborate closely with developers, QA and cross product teams to streamline release processes.
- Best Practices Advocacy: Advise teams on CI/CD pipelines, observability, security compliance, and modern development practices.
- Collaborate with product managers and stakeholders to align technical roadmaps with business strategy
- Expertise in architecture governance, security frameworks, and scalable system design across large organizations
Technical Skills :
- Strong experience with the AWS data stack (S3, Glue, EMR, Lambda, Kinesis, Redshift, Step Functions etc.,).
- Strong hands-on expertise in Scala, PySpark, Spark optimization techniques, HiveQL, and distributed computing.
- Good understanding of Hadoop ecosystem (HDFS, Hive, Spark, YARN, Kafka).
- Good work experience in SQL in hive and impala
- Proficiency in at least one scripting/programming language: Python, Shell scripting.
- Strong experience with CI/CD, GitHub, Git commands.
- Expertise in ETL and Data Warehousing and cloud concepts.
- Good understanding of data modelling (star/snowflake), partitioning strategies, and schema evolution.
- Expertise in data profiling and decision making.
- Able to understand, design and create data flow diagrams and do data modelling. (knowledge of Miro will be added advantage)
- Able to understand the architecture and design end-to-end data flow.
- Hands-on experience with Airflow, or Controlu2011M, or other orchestrators.
- To monitor and support BAU and year end activities, if needed.
- Well versed with security and compliance aspects in Cloud.
- Familiarity with serverless patterns and containerization (Docker, ECS/EKS).
- Experience with monitoring/logging tools and incident management practices.
Other Requirements
- Strong logical and analytical, problem-solving, and communication skills.
- Communicate effectively and concisely with multiple stakeholders and coordinate and collaborate with cross functional teams.
- Ability to support both legacy Hadoop workloads and cloud-first architectures.
- AWS certifications (Data Engineer, Solutions Architect, or Developer) are a plus.
- Strong leadership and mentoring abilities
- Detail-Oriented and proactive in problem-solving and issue resolution
We offer you a competitive total rewards package, continuing education & training, and tremendous potential with a growing worldwide organization.
DISCLAIMER:
Nothing in this job description restricts management's right to assign or reassign duties and responsibilities of this job to other entities including but not limited to subsidiaries, partners, or purchasers of Alight business units.
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